Resources tagged: paper

169 curated 3D resources tagged paper (Tech). Browse all tags.

• 3D Neural Scene Representations for Visuomotor Control paper. Li et al., CoRL 2021 Oral.
  in AI & Machine Learning for CG → Research Papers
• 3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows paper. ArXiv 2022 paper on integrating text-to-image AI in 3D design workflows.
  in AI & Machine Learning for CG → Research Papers
• 4D Gaussian Splatting reference. Dynamic scenes (CVPR 2024).
  in Tools, Pipeline & Utilities → Gaussian Splatting & NeRF
• A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields paper. Park et al., SIGGRAPH Asia 2021. HyperNeRF: lifts NeRF into a higher-dimensional space to handle scenes whose topology changes.
  in AI & Machine Learning for CG → Research Papers
• A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis paper. Pan et al., NeurIPS 2021. ShadeGAN: 3D-aware GAN with explicit lighting and shading for more accurate generated shapes.
  in AI & Machine Learning for CG → Research Papers
• Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models paper. Ling et al., CVPR 2024. Align Your Gaussians generates animated 4D objects from text with dynamic 3D Gaussians.
  in AI & Machine Learning for CG → Research Papers
• AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training paper. Jiang et al., CVPR 2023. Alignment-aware training that reduces misalignment blur so NeRF renders high-resolution detail.
  in AI & Machine Learning for CG → Research Papers
• Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies paper. Peng et al., ICCV 2021. Builds animatable NeRF human models from multi-view video using skeleton-driven deformation fields.
  in AI & Machine Learning for CG → Research Papers
• Animatable Neural Radiance Fields from Monocular RGB Videos paper. Chen et al., arXiv 2021. Builds animatable NeRF human avatars from monocular RGB video using a parametric body model.
  in AI & Machine Learning for CG → Research Papers
• AutoInt: Automatic Integration for Fast Neural Volume Rendering paper. Lindell et al., CVPR 2021. Learns closed-form integrals of volume rendering to speed up neural rendering.
  in AI & Machine Learning for CG → Research Papers
• BeyondPixels: A Review of the Evolution of Neural Radiance Fields paper. AKM Shahariar Azad Rabby and Chengcui Zhang, Arxiv 2023.
  in AI & Machine Learning for CG → Research Papers
• Block-NeRF: Scalable Large Scene Neural View Synthesis paper. Tancik et al., Arxiv 2022.
  in AI & Machine Learning for CG → Research Papers
• BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects paper. Wen et al., CVPR 2023. Jointly tracks the 6-DoF pose of an unknown object and reconstructs its 3D shape from RGB-D video.
  in AI & Machine Learning for CG → Research Papers
• CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representations paper. Dupont et al., 3DV 2022. Network that predicts CAD operation types and their construction steps from B-rep models.
  in AI & Machine Learning for CG → Research Papers
• CLA-NeRF: Category-Level Articulated Neural Radiance Field paper. Tseng et al., ICRA 2022. Category-level NeRF that renders articulated objects and estimates their part poses.
  in AI & Machine Learning for CG → Research Papers
• CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields paper. Wang et al., CVPR 2022. Edits the shape and color of NeRF objects using CLIP text or image prompts.
  in AI & Machine Learning for CG → Research Papers
• CodeNeRF: Disentangled Neural Radiance Fields for Object Categories paper. Jang et al., ICCV 2021. Category-level NeRF with separate shape and texture codes for editing and novel view synthesis.
  in AI & Machine Learning for CG → Research Papers
• Color-NeRF paper. NeRF research paper on color and appearance modelling.
  in AI & Machine Learning for CG → Research Papers
• Consolidating Attention Features for Multi-view Image Editing paper. Patashnik et al., SIGGRAPH 2024. Keeps diffusion image edits consistent across multi-view images of a scene.
  in AI & Machine Learning for CG → Research Papers
• Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion paper. Bhalgat et al., NeurIPS 2023 (**Spotlight**)
  in AI & Machine Learning for CG → Research Papers
• CROSSFIRE: Camera Relocalization On Self-Supervised Features from an Implicit Representation paper. Moreau et al., ICCV 2023. CROSSFIRE relocalizes a camera in real time using a NeRF as the scene map.
  in AI & Machine Learning for CG → Research Papers
• D-NeRF: Neural Radiance Fields for Dynamic Scenes paper. Pumarola et al., CVPR 2021. Extends NeRF with a time-conditioned deformation field to render dynamic scenes from monocular video.
  in AI & Machine Learning for CG → Research Papers
• Deep Generative Models on 3D Representations: A Survey paper. Shi et al., arXiv 2022. Survey of deep generative models across 3D representations such as point clouds, meshes, voxels and neural fields.
  in AI & Machine Learning for CG → Research Papers
• DeepCAD: A Deep Generative Network for Computer-Aided Design Models paper. Wu et al., ICCV 2021. Generative network that outputs CAD models as sequences of sketch and extrude operations.
  in AI & Machine Learning for CG → Research Papers
• Deformable Neural Radiance Fields paper. Park et al., ICCV 2021. Nerfies: adds a learned deformation field to NeRF to capture non-rigid scenes from handheld phone video.
  in AI & Machine Learning for CG → Research Papers
• Depth-supervised NeRF: Fewer Views and Faster Training for Free paper. Deng et al., CVPR 2022. Adds sparse depth from structure-from-motion as supervision so NeRF trains faster with fewer views.
  in AI & Machine Learning for CG → Research Papers
• DeRF: Decomposed Radiance Fields paper. Rebain et al., Arxiv 2020.
  in AI & Machine Learning for CG → Research Papers
• DFNet: Enhance Absolute Pose Regression with Direct Feature Matching paper. Chen et al., ECCV 2022. Improves camera pose regression by matching features against novel views rendered from a NeRF.
  in AI & Machine Learning for CG → Research Papers
• Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction paper. Sun et al., CVPR 2022. Reconstructs radiance fields on explicit voxel grids, converging in minutes instead of hours.
  in AI & Machine Learning for CG → Research Papers
• DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images paper. Wang et al., ICLR 2023. Decomposes NeRF scenes into individual 3D objects from 2D images so they can be moved, rotated or removed.
  in AI & Machine Learning for CG → Research Papers
• DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model paper. Xu et al., ICLR 2024. DMV3D denoises multi-view diffusion with a transformer 3D reconstruction model.
  in AI & Machine Learning for CG → Research Papers
• DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks paper. Neff et al., CGF 2021. Uses a depth oracle network to cut samples per ray for near real-time NeRF rendering.
  in AI & Machine Learning for CG → Research Papers
• Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models paper. Xu et al., CVPR 2023. Zero-shot text-to-3D that uses a 3D shape prior and text-to-image diffusion to guide NeRF optimization.
  in AI & Machine Learning for CG → Research Papers
• DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior paper. Sun et al., ICLR 2024. DreamCraft3D generates 3D objects from a reference image with bootstrapped diffusion.
  in AI & Machine Learning for CG → Research Papers
• DreamFusion: Text-to-3D using 2D Diffusion paper. Poole et al., ICLR 2023. Generates 3D NeRF models from text by optimizing them with a pretrained 2D diffusion model via score distillation.
  in AI & Machine Learning for CG → Research Papers
• DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation paper. Tang et al., ICLR 2024. DreamGaussian generates textured 3D meshes from text or images in minutes with Gaussian splatting.
  in AI & Machine Learning for CG → Research Papers
• DreamGaussian4D: Generative 4D Gaussian Splatting paper. Ren et al., arXiv 2023. DreamGaussian4D generates animated 4D content quickly with Gaussian splatting.
  in AI & Machine Learning for CG → Research Papers
• DreamWaltz: Make a Scene with Complex 3D Animatable Avatars paper. Huang et al., NeurIPS 2023. DreamWaltz generates animatable 3D avatars from text with a human body prior.
  in AI & Machine Learning for CG → Research Papers
• DyLiN: Making Light Field Networks Dynamic paper. Yu et al., CVPR 2023. Extends light field networks to dynamic scenes for fast rendering of deforming content.
  in AI & Machine Learning for CG → Research Papers
• Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction paper. Gafni et al., CVPR 2021. Dynamic NeRF conditioned on expression parameters to build 4D facial avatars from monocular video.
  in AI & Machine Learning for CG → Research Papers
• DynIBaR: Neural Dynamic Image-Based Rendering paper. Li et al., CVPR 2023. Image-based rendering method for novel view synthesis from long monocular videos of dynamic scenes.
  in AI & Machine Learning for CG → Research Papers
• Editable Free-viewpoint Video Using a Layered Neural Representation paper. Zhang et al., SIGGRAPH 2021. Layered neural representation of free-viewpoint video that lets performers be moved, scaled or removed.
  in AI & Machine Learning for CG → Research Papers
• Editing Conditional Radiance Fields paper. Liu et al., ICCV 2021. Conditional radiance fields that let users edit shape and color of object categories with a few scribbles.
  in AI & Machine Learning for CG → Research Papers
• En3D: An Enhanced Generative Model for Sculpting 3D Humans from 2D Synthetic Data paper. Men et al., CVPR 2024. En3D generates realistic 3D human avatars from synthetic 2D data.
  in AI & Machine Learning for CG → Research Papers
• EndoGaussian: Real-time Gaussian Splatting for Dynamic Endoscopic Scene Reconstruction paper. Liu et al., arXiv 2024. EndoGaussian reconstructs dynamic endoscopic surgical scenes in real time with Gaussian splatting.
  in AI & Machine Learning for CG → Research Papers
• ENeRF: Efficient Neural Radiance Fields for Interactive Free-viewpoint Video paper. Lin et al., SIGGRAPH Asia 2022. Generalizable NeRF using cascaded cost volumes for interactive free-viewpoint video of dynamic scenes.
  in AI & Machine Learning for CG → Research Papers
• FastNeRF: High-Fidelity Neural Rendering at 200FPS paper. Garbin et al., Arxiv 2021.
  in AI & Machine Learning for CG → Research Papers
• FiG-NeRF: Figure Ground Neural Radiance Fields for 3D Object Category Modelling paper. Xie et al., 3DV 2021. Separates foreground objects from background with two NeRFs to model 3D object categories.
  in AI & Machine Learning for CG → Research Papers
• From 2D CAD Drawings to 3D Parametric Models: A Vision-Language Approach paper. Wang et al., AAAI 2025. CAD2Program reconstructs 3D parametric models from 2D CAD drawings with a vision-language model.
  in AI & Machine Learning for CG → Research Papers
• GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting paper. Zhou et al., ICML 2024. GALA3D generates complex text-to-3D scenes from LLM layouts with Gaussian splatting.
  in AI & Machine Learning for CG → Research Papers
• GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation paper. Chng et al., ECCV 2022. Radiance field with Gaussian activations that jointly reconstructs the scene and estimates camera poses.
  in AI & Machine Learning for CG → Research Papers
• GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians paper. Qian et al., CVPR 2024. GaussianAvatars builds photoreal head avatars from 3D Gaussians rigged to a face model.
  in AI & Machine Learning for CG → Research Papers
• GaussianObject: High-Quality 3D Object Reconstruction from Four Views with Gaussian Splatting paper. Yang et al., SIGGRAPH Asia 2024. GaussianObject reconstructs 3D objects from four views with Gaussian splatting.
  in AI & Machine Learning for CG → Research Papers
• Gemini Robotics 1.5 paper. Embodied reasoning, thinking, and motion transfer.
  in AI & Machine Learning for CG → Research Papers
• Generative Occupancy Fields for 3D Surface-Aware Image Synthesis paper. Xu et al., NeurIPS 2021. Combines occupancy and radiance fields in a 3D-aware GAN for more accurate surfaces.
  in AI & Machine Learning for CG → Research Papers
• GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields paper. Niemeyer et al., CVPR 2021.
  in AI & Machine Learning for CG → Research Papers
• GNeRF: GAN-based Neural Radiance Field without Posed Camera paper. Meng et al., ICCV 2021. GAN-based NeRF that trains on images with unknown or random camera poses.
  in AI & Machine Learning for CG → Research Papers
• GO-NeRF: Generating Objects in Neural Radiance Fields for Virtual Reality Content Creation paper. Dai et al., arXiv 2024. GO-NeRF generates 3D objects placed inside existing NeRF scenes for VR content.
  in AI & Machine Learning for CG → Research Papers
• GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis paper. Schwarz et al., NeurIPS 2020. Generative radiance field model that synthesizes 3D-consistent images from unposed 2D image collections.
  in AI & Machine Learning for CG → Research Papers
• GRF: Learning a General Radiance Field for 3D Scene Representation and Rendering paper. Trevithick and Yang, ICCV 2021. Learns a general radiance field from 2D image features that renders novel views of unseen scenes.
  in AI & Machine Learning for CG → Research Papers
• Ha-NeRF: Hallucinated Neural Radiance Fields in the Wild paper. Chen et al., CVPR 2022. Builds NeRFs from in-the-wild photo collections, handling appearance changes and transient occluders.
  in AI & Machine Learning for CG → Research Papers
• HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video paper. Weng et al., CVPR 2022. Renders moving people from new viewpoints using a NeRF trained on a single monocular video.
  in AI & Machine Learning for CG → Research Papers
• IBRNet: Learning Multi-View Image-Based Rendering paper. Wang et al., CVPR 2021. Learns to blend nearby source views for image-based rendering that generalizes to unseen scenes.
  in AI & Machine Learning for CG → Research Papers
• IDE-3D: Interactive Disentangled Editing for High-Resolution 3D-aware Portrait Synthesis paper. Sun et al., SIGGRAPH Asia 2022. 3D-aware GAN for high-resolution portraits with interactive, disentangled editing of shape, texture and pose.
  in AI & Machine Learning for CG → Research Papers
• Image Sculpting: Precise Object Editing with 3D Geometry Control paper. Yenphraphai et al., CVPR 2024. Image Sculpting edits 2D objects by lifting them to 3D geometry.
  in AI & Machine Learning for CG → Research Papers
• Importance Sampling for Production Rendering paper. SIGGRAPH course notes on importance sampling for production rendering.
  in AI & Machine Learning for CG → Research Papers
• In-Place Scene Labelling and Understanding with Implicit Scene Representation paper. Zhi et al., ICCV 2021. Semantic-NeRF: adds semantic labels to a radiance field to propagate sparse labels across a scene.
  in AI & Machine Learning for CG → Research Papers
• iNeRF: Inverting Neural Radiance Fields for Pose Estimation paper. Yen-Chen et al. IROS 2021.
  in AI & Machine Learning for CG → Research Papers
• InfNeRF: Towards Infinite Scale NeRF Rendering with O(log n) Space Complexity paper. Liang et al., SIGGRAPH Asia 2024. Octree-based level-of-detail NeRF that renders very large scenes with O(log n) memory.
  in AI & Machine Learning for CG → Research Papers
• Instant3D: Instant Text-to-3D Generation paper. Li et al., arXiv 2023. Instant3D generates 3D objects from text in one feed-forward pass, without per-prompt optimization.
  in AI & Machine Learning for CG → Research Papers
• KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs paper. Reiser et al., ICCV 2021. Splits a NeRF into thousands of tiny MLPs to render orders of magnitude faster.
  in AI & Machine Learning for CG → Research Papers
• KiloNeuS: Implicit Neural Representations with Real-Time Global Illumination paper. Esposito et al., Arxiv 2022.
  in AI & Machine Learning for CG → Research Papers
• L2G-NeRF: Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields paper. Chen et al., CVPR 2023. Bundle-adjusting NeRF that registers cameras locally per pixel before global alignment.
  in AI & Machine Learning for CG → Research Papers
• Learned Initializations for Optimizing Coordinate-Based Neural Representations paper. Tancik et al., CVPR 2021. Meta-learns initial weights for coordinate-based networks so they fit new signals in fewer steps.
  in AI & Machine Learning for CG → Research Papers
• Learning Compositional Radiance Fields of Dynamic Human Heads paper. Wang et al., CVPR 2021. Hybrid voxel and MLP radiance field for rendering dynamic human heads with fine detail.
  in AI & Machine Learning for CG → Research Papers
• Learning Neural Transmittance for Efficient Rendering of Reflectance Fields paper. Mohammad Shafiei et al., BMVC 2021.
  in AI & Machine Learning for CG → Research Papers
• Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering paper. Yang et al., ICCV 2021. Object-compositional NeRF that lets individual objects in a scene be moved, duplicated or removed.
  in AI & Machine Learning for CG → Research Papers
• Learning the 3D Fauna of the Web paper. Li et al., CVPR 2024. 3D-Fauna learns a deformable 3D model of 100+ animal species from web images.
  in AI & Machine Learning for CG → Research Papers
• Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous Driving paper. Cao et al., ICRA 2024. Lightning NeRF is a hybrid scene representation for fast NeRF training in driving scenes.
  in AI & Machine Learning for CG → Research Papers
• Loc-NeRF: Monte Carlo Localization using Neural Radiance Fields paper. Maggio et al., ICRA 2023. Robot localization method that runs a Monte Carlo particle filter against a pretrained NeRF map.
  in AI & Machine Learning for CG → Research Papers
• Local 3D Editing via 3D Distillation of CLIP Knowledge paper. Hyung et al., CVPR 2023. Edits local regions of 3D-aware GAN outputs by distilling CLIP knowledge.
  in AI & Machine Learning for CG → Research Papers
• M3DBench: Let's Instruct Large Models with Multi-modal 3D Prompts paper. Li et al., arXiv 2023. M3DBench is a benchmark for instructing large models with multi-modal 3D prompts.
  in AI & Machine Learning for CG → Research Papers
• Magic3D: High-Resolution Text-to-3D Content Creation paper. Lin et al., CVPR 2023. Two-stage coarse-to-fine text-to-3D method that produces high-resolution textured meshes.
  in AI & Machine Learning for CG → Research Papers
• Make-A-Character: High Quality Text-to-3D Character Generation within Minutes paper. Ren et al., arXiv 2023. Make-A-Character creates lifelike 3D character avatars from text descriptions.
  in AI & Machine Learning for CG → Research Papers
• Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior paper. Tang et al., ICCV 2023. Make-It-3D creates textured 3D objects from a single image using a 2D diffusion prior.
  in AI & Machine Learning for CG → Research Papers
• MinD-3D: Reconstruct High-quality 3D objects in Human Brain paper. Gao et al., ECCV 2024. MinD-3D reconstructs 3D objects from fMRI brain signals.
  in AI & Machine Learning for CG → Research Papers
• MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis paper. Li et al., ICCV 2021. Combines multiplane images with NeRF to predict continuous-depth MPIs from a single image.
  in AI & Machine Learning for CG → Research Papers
• Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields paper. Barron et al., Arxiv 2022.
  in AI & Machine Learning for CG → Research Papers
• Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields paper. Barron et al., ICCV 2021. Renders anti-aliased cones instead of rays so NeRF handles multiple scales without aliasing.
  in AI & Machine Learning for CG → Research Papers
• Mixture of Volumetric Primitives for Efficient Neural Rendering paper. Lombardi et al., SIGGRAPH 2021.
  in AI & Machine Learning for CG → Research Papers
• MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo paper. Chen et al., ICCV 2021. Uses multi-view stereo cost volumes so radiance fields generalize to new scenes from three input views.
  in AI & Machine Learning for CG → Research Papers
• NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes paper. Irshad et al., ICCV 2023. NeO 360 synthesizes novel views of outdoor scenes from a few input images.
  in AI & Machine Learning for CG → Research Papers
• NeRF reference. Mildenhall et al., 2020. Original NeRF reference implementation.
  in Tools, Pipeline & Utilities → Photogrammetry & 3D Scanning
• NeRF (paper site) paper. Mildenhall et al., ECCV 2020. The original NeRF: an MLP that maps 5D coordinates to color and density for novel view synthesis.
  in AI & Machine Learning for CG → Research Papers
• NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images paper. Ben Mildenhall et al, arXiv 2021.
  in AI & Machine Learning for CG → Research Papers
• NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections paper. Martin-Brualla et al., CVPR 2021.
  in AI & Machine Learning for CG → Research Papers
• NeRF--: Neural Radiance Fields Without Known Camera Parameters paper. Wang et al., arXiv 2021. Trains NeRF while jointly estimating camera intrinsics and extrinsics from forward-facing images.
  in AI & Machine Learning for CG → Research Papers
• NeRF-In: Free-Form NeRF Inpainting with RGB-D Priors paper. Liu et al., arXiv 2022. Removes user-selected objects from a NeRF scene using RGB-D inpainting priors.
  in AI & Machine Learning for CG → Research Papers
• NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields paper. Irshad et al., ECCV 2024. NeRF-MAE pretrains masked autoencoders on NeRF grids for 3D representation learning.
  in AI & Machine Learning for CG → Research Papers
• NeRF-SOS: Any-view Self-supervised Object Segmentation on Complex Real-world Scenes paper. Fan et al., ICLR 2023. Self-supervised object segmentation that works from any view of complex real-world scenes using NeRF.
  in AI & Machine Learning for CG → Research Papers
• NeRF-VAE: A Geometry Aware 3D Scene Generative Model paper. Kosiorek et al., Arxiv 2021.
  in AI & Machine Learning for CG → Research Papers
• NeRF: Neural Radiance Field in 3D Vision, Introduction and Review paper. Kyle Gao, Yina Gao, Hongjie He, Dening Lu, Linlin Xu, Jonathan Li.
  in AI & Machine Learning for CG → Research Papers
• NeRF++: Analyzing and Improving Neural Radiance Fields paper. Zhang et al., arXiv 2020. Analyzes NeRF and adds an inverted-sphere background model for unbounded 360-degree scenes.
  in AI & Machine Learning for CG → Research Papers
• NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo paper. Wei et al., ICCV 2021. Guides NeRF optimization with monocular depth priors for indoor multi-view stereo reconstruction.
  in AI & Machine Learning for CG → Research Papers
• NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis paper. Srinivasan et al. CVPR 2021.
  in AI & Machine Learning for CG → Research Papers
• Neural 3D Video Synthesis from Multi-view Video paper. Li et al., CVPR 2022. Dynamic NeRF conditioned on latent codes that renders novel views of multi-view video.
  in AI & Machine Learning for CG → Research Papers
• Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans paper. Peng et al., CVPR 2021. Anchors latent codes to a deformable body mesh to render dynamic humans from sparse multi-view video.
  in AI & Machine Learning for CG → Research Papers
• Neural Radiance Flow for 4D View Synthesis and Video Processing paper. Du et al., ICCV 2021. Learns a 4D radiance and flow field for view synthesis and video processing such as denoising and super-resolution.
  in AI & Machine Learning for CG → Research Papers
• Neural Rays for Occlusion-aware Image-based Rendering paper. Liu et al., CVPR 2022. Image-based rendering that predicts visibility per ray to handle occlusions when synthesizing novel views.
  in AI & Machine Learning for CG → Research Papers
• Neural Refinement for Absolute Pose Regression with Feature Synthesis paper. Chen et al., CVPR 2024. Refines camera pose regression at test time using features rendered from a neural feature field.
  in AI & Machine Learning for CG → Research Papers
• Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes paper. Li et al., CVPR 2021. Models dynamic scenes as time-varying scene flow fields for space-time view synthesis from monocular video.
  in AI & Machine Learning for CG → Research Papers
• Neural Scene Graphs for Dynamic Scenes paper. Ost et al., CVPR 2021. Decomposes dynamic scenes like driving footage into a learned scene graph of moving objects.
  in AI & Machine Learning for CG → Research Papers
• Neural Sparse Voxel Fields paper. Liu et al., NeurIPS 2020. Organizes a radiance field into a sparse voxel octree to skip empty space and render faster.
  in AI & Machine Learning for CG → Research Papers
• Neural Volume Rendering: NeRF paper. Dellaert and Yen-Chen, arXiv 2020. Survey of the NeRF paper and the wave of neural volume rendering work that followed it.
  in AI & Machine Learning for CG → Research Papers
• NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction paper. Wang et al., NeurIPS 2021. Represents surfaces as signed distance functions trained with volume rendering for multi-view reconstruction.
  in AI & Machine Learning for CG → Research Papers
• Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Deforming Scene from Monocular Video paper. Tretschk et al., ICCV 2021. Reconstructs deforming scenes from monocular video with a NeRF plus a learned ray-bending deformation field.
  in AI & Machine Learning for CG → Research Papers
• NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior paper. Bian et al., CVPR 2023. Trains NeRF without pose priors by using monocular depth to constrain relative camera poses.
  in AI & Machine Learning for CG → Research Papers
• One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion paper. Liu et al., CVPR 2024. One-2-3-45++ turns a single image into a textured 3D mesh in about a minute.
  in AI & Machine Learning for CG → Research Papers
• ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds paper. Sharma et al., ECCV 2020. Network that segments point clouds and fits parametric surfaces such as B-splines and primitives.
  in AI & Machine Learning for CG → Research Papers
• PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds paper. Liu et al., ICLR 2021. Network that extracts 3D wireframes of vertices and edges directly from raw point clouds.
  in AI & Machine Learning for CG → Research Papers
• pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis paper. Chan et al., CVPR 2021. 3D-aware GAN using SIREN periodic activations in a radiance field to generate view-consistent images.
  in AI & Machine Learning for CG → Research Papers
• pixelNeRF: Neural Radiance Fields from One or Few Images paper. Yu et al., CVPR 2021. Conditions NeRF on image features so it predicts radiance fields from one or a few input images.
  in AI & Machine Learning for CG → Research Papers
• PlankAssembly: 3D Reconstruction from Three Orthographic Views with Learnt Shape Programs paper. Hu et al., ICCV 2023. PlankAssembly turns three orthographic line drawings into 3D CAD models.
  in AI & Machine Learning for CG → Research Papers
• PlenOctrees for Real-time Rendering of Neural Radiance Fields paper. Yu et al., ICCV 2021. Bakes NeRFs into octrees of spherical harmonics for real-time rendering.
  in AI & Machine Learning for CG → Research Papers
• Point-NeRF: Point-based Neural Radiance Fields paper. Xu et al., CVPR 2022. Uses neural point clouds to model radiance fields, initialized from multi-view stereo for fast training.
  in AI & Machine Learning for CG → Research Papers
• Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinders paper. Uy et al., CVPR 2022. Reverse-engineers point clouds into editable CAD by fitting sketch-and-extrude cylinders.
  in AI & Machine Learning for CG → Research Papers
• PolyGen: An Autoregressive Generative Model of 3D Meshes paper. Nash et al., ICML 2020. Transformer that generates 3D meshes directly as sequences of vertices and faces.
  in AI & Machine Learning for CG → Research Papers
• Ponder: Point Cloud Pre-training via Neural Rendering paper. Huang et al., ICCV 2023. Pre-trains point cloud encoders by rendering color and depth images through differentiable neural rendering.
  in AI & Machine Learning for CG → Research Papers
• PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm paper. Zhu et al., arXiv 2023. PonderV2 is a universal pretraining method for 3D foundation models.
  in AI & Machine Learning for CG → Research Papers
• PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction paper. Bian et al., ICLR 2024. Learns a pose residual field to refine camera poses for more accurate neural surface reconstruction.
  in AI & Machine Learning for CG → Research Papers
• Portrait Neural Radiance Fields from a Single Image paper. Gao et al., arXiv 2020. Meta-learned NeRF that reconstructs a portrait radiance field from a single headshot.
  in AI & Machine Learning for CG → Research Papers
• Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts paper. Cheng et al., ICLR 2024. Progressive3D edits text-to-3D content region by region for complex prompts.
  in AI & Machine Learning for CG → Research Papers
• PSAvatar: A Point-based Shape Model for Real-Time Head Avatar Animation with 3D Gaussian Splatting paper. Zhao et al., arXiv 2024. PSAvatar animates real-time head avatars with a point-based model and 3D Gaussians.
  in AI & Machine Learning for CG → Research Papers
• Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis paper. Matthew Tancik et al., Arxiv 2021.
  in AI & Machine Learning for CG → Research Papers
• PVA: Pixel-aligned Volumetric Avatars paper. Raj et al., CVPR 2021. Builds volumetric head avatars from a few input views using pixel-aligned features.
  in AI & Machine Learning for CG → Research Papers
• PVDeconv: Point-voxel deconvolution for autoencoding cad construction in 3D paper. Cherenkova et al., ICIP 2020. Point-voxel deconvolution autoencoder that reconstructs CAD models from 3D scans.
  in AI & Machine Learning for CG → Research Papers
• Reconstructing Editable Prismatic CAD from Rounded Voxel Models paper. Lambourne et al., SIGGRAPH Asia 2022. Converts rounded voxel shapes into editable prismatic CAD models built from extruded sketches.
  in AI & Machine Learning for CG → Research Papers
• Recovering HDR Radiance Maps (Debevec & Malik, 1997) paper. SIGGRAPH 1997 paper. Original HDR-from-bracketed-exposures recovery method.
  in AI & Machine Learning for CG → Research Papers
• Rendering Synthetic Objects into Real Scenes (Debevec, 1998) paper. SIGGRAPH 1998 paper founding image-based lighting.
  in AI & Machine Learning for CG → Research Papers
• RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D paper. Qiu et al., CVPR 2024. RichDreamer uses a normal-depth diffusion model for detailed text-to-3D.
  in AI & Machine Learning for CG → Research Papers
• Rig3DGS: Creating Controllable Portraits from Casual Monocular Videos paper. Rivero et al., arXiv 2024. Rig3DGS builds controllable 3D Gaussian portraits from casual phone videos.
  in AI & Machine Learning for CG → Research Papers
• Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion paper. Wang et al., CVPR 2023. Diffusion model that generates 3D digital avatars as neural radiance fields, including from text or a photo.
  in AI & Machine Learning for CG → Research Papers
• RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering paper. Li et al., ICCAD 2022. Algorithm and hardware co-design for real-time NeRF rendering on edge devices aimed at AR and VR.
  in AI & Machine Learning for CG → Research Papers
• SEEAvatar: Photorealistic Text-to-3D Avatar Generation with Constrained Geometry and Appearance paper. Xu et al., arXiv 2023. SEEAvatar generates photoreal 3D avatars from text with constrained geometry and appearance.
  in AI & Machine Learning for CG → Research Papers
• Self-Calibrating Neural Radiance Fields paper. Jeong et al., ICCV 2021. Jointly learns scene geometry and camera calibration, including lens distortion, without a calibration target.
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• SIGNeRF: Scene Integrated Generation for Neural Radiance Fields paper. Dihlmann et al., CVPR 2024. SIGNeRF generates and edits objects inside existing NeRF scenes.
  in AI & Machine Learning for CG → Research Papers
• SINE: Semantic-driven Image-based NeRF Editing with Prior-guided Editing Field paper. Bao et al., CVPR 2023. Edits a NeRF from a single edited image using semantic and geometric priors.
  in AI & Machine Learning for CG → Research Papers
• SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image paper. Xu et al., ECCV 2022. Trains a NeRF on complex scenes from a single image using semi-supervised geometry and semantic losses.
  in AI & Machine Learning for CG → Research Papers
• Space-time Neural Irradiance Fields for Free-Viewpoint Video paper. Xian et al., CVPR 2021. Space-time irradiance field that renders free-viewpoint video from a single monocular video plus depth.
  in AI & Machine Learning for CG → Research Papers
• Streaming Radiance Fields for 3D Video Synthesis paper. Li et al., NeurIPS 2022. Streams radiance fields frame by frame to reconstruct and render free-viewpoint 3D video.
  in AI & Machine Learning for CG → Research Papers
• Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting paper. Yan et al., ECCV 2024. Street Gaussians models dynamic urban driving scenes with Gaussian splatting.
  in AI & Machine Learning for CG → Research Papers
• StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis paper. Gu et al., ICLR 2022. Style-based 3D-aware generator combining NeRF and StyleGAN to synthesize high-resolution, view-consistent images.
  in AI & Machine Learning for CG → Research Papers
• Supervised Fitting of Geometric Primitives to 3D Point Clouds paper. Li et al., CVPR 2019. SPFN: supervised network that fits geometric primitives such as planes, spheres and cylinders to point clouds.
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• SurfelNeRF: Neural Surfel Radiance Fields for Online Photorealistic Reconstruction of Indoor Scenes paper. Gao et al., CVPR 2023. SurfelNeRF reconstructs and renders indoor scenes online with neural surfels.
  in AI & Machine Learning for CG → Research Papers
• Switch-NeRF: Learning Scene Decomposition with Mixture of Experts for Large-scale Neural Radiance Fields paper. Mi et al., ICLR 2023. Mixture-of-experts NeRF that learns to split large-scale scenes into sub-networks.
  in AI & Machine Learning for CG → Research Papers
• Taming Mode Collapse in Score Distillation for Text-to-3D Generation paper. Wang et al., arXiv 2023. Reduces multi-face Janus artifacts in score distillation text-to-3D generation.
  in AI & Machine Learning for CG → Research Papers
• Text-To-4D Dynamic Scene Generation paper. Singer et al., ICML 2023. MAV3D generates dynamic 3D scenes from text with a 4D NeRF and text-to-video diffusion.
  in AI & Machine Learning for CG → Research Papers
• Text2CAD: Text to 3D CAD Generation via Technical Drawings paper. Yavartanoo et al., arXiv 2024. Text2CAD generates 3D CAD models from text by first producing technical drawings.
  in AI & Machine Learning for CG → Research Papers
• TextField3D: Towards Enhancing Open-Vocabulary 3D Generation with Noisy Text Fields paper. Huang et al., ICLR 2024. TextField3D adds noisy text fields for open-vocabulary 3D generation.
  in AI & Machine Learning for CG → Research Papers
• TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusion paper. Yeh et al., CVPR 2024. TextureDreamer transfers relightable textures from 3 to 5 photos onto 3D shapes.
  in AI & Machine Learning for CG → Research Papers
• TiNeuVox: Fast Dynamic Radiance Fields with Time-Aware Neural Voxels paper. Fang et al., SIGGRAPH Asia 2022. Time-aware voxel features that train dynamic radiance fields in minutes.
  in AI & Machine Learning for CG → Research Papers
• TOSS:High-quality Text-guided Novel View Synthesis from a Single Image paper. Shi et al., arXiv 2023. TOSS adds text guidance to novel view synthesis from a single image.
  in AI & Machine Learning for CG → Research Papers
• Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers paper. Zou et al., CVPR 2024. Reconstructs 3D Gaussians from a single image with a triplane transformer.
  in AI & Machine Learning for CG → Research Papers
• UV Volumes for Real-time Rendering of Editable Free-view Human Performance paper. Chen et al., CVPR 2023. Encodes human performances in UV volumes so free-view video renders in real time and can be retextured.
  in AI & Machine Learning for CG → Research Papers
• ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields paper. Dong et al., NeurIPS 2023. ViCA-NeRF edits NeRF scenes from text instructions with multi-view consistency.
  in AI & Machine Learning for CG → Research Papers
• Volume Rendering of Neural Implicit Surfaces paper. Yariv et al., NeurIPS 2021. VolSDF: models density as a function of signed distance for better surface reconstruction with volume rendering.
  in AI & Machine Learning for CG → Research Papers
• Wonder3D: Single Image to 3D using Cross-Domain Diffusion paper. Long et al., CVPR 2024. Wonder3D generates textured meshes from a single image with cross-domain diffusion.
  in AI & Machine Learning for CG → Research Papers
• X-NeRF: Explicit Neural Radiance Field for Multi-Scene 360° Insufficient RGB-D Views paper. Zhu et al., WACV 2023. Explicit radiance field that reconstructs multiple 360-degree scenes from sparse, insufficient RGB-D views.
  in AI & Machine Learning for CG → Research Papers
• Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model paper. Shi et al., arXiv 2023. Zero123++ generates consistent multi-view images from one input image for 3D creation.
  in AI & Machine Learning for CG → Research Papers