3D-Shape-Analysis-Paper-List

A list of papers, libraries and datasets I recently read is collected for anyone who shows interest at 3D detection, shape representation, shape completion, shape reconstruction, 3D scene understanding, 3D scene reconstruction.

Statistics: 🔥 code is available & stars >= 100 | ⭐ citation >= 50

3D Detection

[CVPR2020] Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation [pytorch]
[Arxiv] SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds [github]
[CVPR2020] End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection [github]
[Arxiv] Finding Your (3D) Center: 3D Object Detection Using a Learned Loss
[CVPR2020] PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
[CVPR2020] 3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segm
[CVPR2020] Fusion-Aware Point Convolution for Online Semantic 3D Scene Segmentation
[CVPR2020] OccuSeg: Occupancy-aware 3D Instance Segmentation
[CVPR2020] Learning to Segment 3D Point Clouds in 2D Image Space
[CVPR2020] Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud [tensorflow]
[AAAI2020] ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection
[Arxiv] MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationships
[Arxiv] HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection
[Arxiv] SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
[Arxiv] 3DSSD: Point-based 3D Single Stage Object Detector
[Arxiv] Monocular 3D Object Detection with Decoupled Structured Polygon Estimation and Height-Guided Depth Estimation
[Arxiv] ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
[Arxiv] A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators
[Arxiv] ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
[Arxiv] Objects as Points [github] ⭐🔥
[Arxiv] RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving [github]
[Arxiv] DSGN: Deep Stereo Geometry Network for 3D Object Detection [github]
[Arxiv] Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation
[Arxiv] PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
[Arxiv] Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots
[Arxiv] SESS: Self-Ensembling Semi-Supervised 3D Object Detection
[NeurIPS2019] PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points
[NeurIPS2019] Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
[ICCV2019] Deep Hough Voting for 3D Object Detection in Point Clouds
[AAAI2020] JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds
[ICCV2019] M3D-RPN: Monocular 3D Region Proposal Network for Object Detection [pytorch]
[ICCV2019] 3D Instance Segmentation via Multi-Task Metric Learning
[Arxiv] Single-Stage Monocular 3D Object Detection with Virtual Cameras
[Arxiv] Depth Completion via Deep Basis Fitting
[Arxiv] Relation Graph Network for 3D Object Detection in Point Clouds
[CVPR2019] 3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans [pytorch] 🔥
[ICCV2019] Rescan: Inductive Instance Segmentation for Indoor RGBD Scans [C++]
[ICCV2019] Transferable Semi-Supervised 3D Object Detection From RGB-D Data
[ICCV2019] STD: Sparse-to-Dense 3D Object Detector for Point Cloud
[ICCV2019] Transferable Semi-Supervised 3D Object Detection From RGB-D Data
[CVPR2019] PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud [pytorch]
[Arxiv] Fast Point R-CNN
[Arxiv] Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection [pytorch] 🔥

Shape Representation

[CVPR2020] Learning Generative Models of Shape Handles [Project page]
[CVPR2020] DualSDF: Semantic Shape Manipulation using a Two-Level Representation [github]
[CVPR2020] Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image [pytorch]
[Arxiv] Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions
[Arxiv] Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds
[Arxiv] Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction
[Arxiv] SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates
[CVPR2020] D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
[Arxiv] Implicit Geometric Regularization for Learning Shapes
[Arxiv] Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface Networks
[Arxiv] Adversarial Generation of Continuous Implicit Shape Representations [pytorch]
[Arxiv] A Novel Tree-structured Point Cloud Dataset For Skeletonization Algorithm Evaluation [dataset]
[CVPRW2019] SkelNetOn 2019: Dataset and Challenge on Deep Learning for Geometric Shape Understanding [project]
[Arxiv] Skeleton Extraction from 3D Point Clouds by Decomposing the Object into Parts
[Arxiv] InSphereNet: a Concise Representation and Classification Method for 3D Object
[Arxiv] Deep Structured Implicit Functions
[CVIU] 3D articulated skeleton extraction using a single consumer-grade depth camera
[ICLR2019] Point Cloud GAN [tensorflow]
[ICCV2019] Learning Shape Templates with Structured Implicit Functions
[ICCV2019] 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions [pytorch]
[ICCV2019] Implicit Surface Representations as Layers in Neural Networks
[CVPR2019] DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation [pytorch] 🔥 ⭐
[SIGGRAPH2019] StructureNet: Hierarchical Graph Networks for 3D Shape Generation [pytorch]
[SIGGRAPH Asia2019] LOGAN: Unpaired Shape Transform in Latent Overcomplete Space [tensorflow]
[TOG] Voxel Cores: Efficient, robust, and provably good approximation of 3D medial axes
[SIGGRAPH2018] P2P-NET: Bidirectional Point Displacement Net for Shape Transform [tensorflow]
[ICML2018] Learning Representations and Generative Models for 3D Point Clouds [tensorflow] 🔥⭐
[NeurIPS2018] Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning [tensorflow][project page]:star::fire:
[AAAI2018] Unsupervised Articulated Skeleton Extraction from Point Set Sequences Captured by a Single Depth Camera
[3DV2018] Parsing Geometry Using Structure-Aware Shape Templates
[SIGGRAPH2017] GRASS: Generative Recursive Autoencoders for Shape Structures [pytorch] 🔥
[TOG] Erosion Thickness on Medial Axes of 3D Shapes
[Vis Comput] Distance field guided L1-median skeleton extraction
[CGF] Contracting Medial Surfaces Isotropically for Fast Extraction of Centred Curve Skeletons
[CGF] Improved Use of LOP for Curve Skeleton Extraction
[SIGGRAPH Asia2015] Deep Points Consolidation [C++ & Qt]
[SIGGRAPH2015] Burning The Medial Axis
[SIGGRAPH2009] Curve Skeleton Extraction from Incomplete Point Cloud [matlab] ⭐
[TOG] SDM-NET: deep generative network for structured deformable mesh
[TOG] Robust and Accurate Skeletal Rigging from Mesh Sequences 🔥
[TOG] L₁-medial skeleton of point cloud [C++] 🔥
[EUROGRAPHICS2016] 3D Skeletons: A State-of-the-Art Report 🔥
[SGP2012] Mean Curvature Skeletons [C++] 🔥
[SMIC2010] Point Cloud Skeletons via Laplacian-Based Contraction [Matlab] 🔥

Shape Completion

[CVPR2020] Cascaded Refinement Network for Point Cloud Completion [github]
[Arxiv] Anisotropic Convolutional Networks for 3D Semantic Scene Completion [github]
[AAAI2020] Attention-based Multi-modal Fusion Network for Semantic Scene Completion
[CVPR2020] 3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior [github]
[Arxiv] Multimodal Shape Completion via Conditional Generative Adversarial Networks
[Arxiv] 3D-SIC: 3D SEMANTIC INSTANCE COMPLETION FOR RGB-D SCANS
[Arxiv] Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion
[Arxiv] PF-Net: Point Fractal Network for 3D Point Cloud Completion
[Arxiv] 3D Gated Recurrent Fusion for Semantic Scene Completion
[ICCVW2019] EdgeConnect: Structure Guided Image Inpainting using Edge Prediction [pytorch] 🔥⭐
[ICRA2020] Depth Based Semantic Scene Completion with Position Importance Aware Loss
[Arxiv] SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans
[Arxiv] PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes
[Arxiv] Unpaired Point Cloud Completion on Real Scans using Adversarial Training [tensorflow]
[AAAI2020] Morphing and Sampling Network for Dense Point Cloud Completion [pytorch]
[ICCVW2019] Render4Completion: Synthesizing Multi-View Depth Maps for 3D Shape Completion
[ICCV2019] ForkNet: Multi-branch Volumetric Semantic Completion from a Single Depth Image [tensorflow]
[ICCV2019] Cascaded Context Pyramid for Full-Resolution 3D Semantic Scene Completion [Caffe3D]
[ICCV2019] Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction
[Arxiv] EdgeNet: Semantic Scene Completion from RGB-D images
[CVPR2019] TopNet: Structural Point Cloud Decoder [pytorch & tensorflow]
[CVPR2019] Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image
[CVPR2019] Leveraging Shape Completion for 3D Siamese Tracking [pytorch]
[CVPR2019] RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion [pytorch]
[3DV2018] PCN: Point Completion Network [tensorflow] 🔥
[ECCV2018] Efficient Semantic Scene Completion Network with Spatial Group Convolution [pytorch]
[CVPR2018] ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans [tensorflow] 🔥⭐
[CVPR2018] Learning 3D Shape Completion from Laser Scan Data with Weak Supervision [torch][torch]
[IJCV2018] Learning 3D Shape Completion under Weak Supervision [torch][torch]
[ICCV2017] High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference ⭐
[ICCV2017] Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis [torch] 🔥⭐
[CVPR2017] Semantic Scene Completion from a Single Depth Image [caffe] 🔥⭐
[CVPR2016] Structured Prediction of Unobserved Voxels From a Single Depth Image [resource] ⭐

Shape Reconstruction

[Arxiv] Combinatorial 3D Shape Generation via Sequential Assembly
[Arxiv] Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
[Arxiv] Neural Object Descriptors for Multi-View Shape Reconstruction
[CVPR2020] SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings [pytorch]
[Arxiv] Modeling 3D Shapes by Reinforcement Learning
[Arxiv] ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds
[Arxiv] Self-Supervised 2D Image to 3D Shape Translation with Disentangled Representations
[Arxiv] Universal Differentiable Renderer for Implicit Neural Representations
[Arxiv] Learning 3D Part Assembly from a Single Image
[Arxiv] Curriculum DeepSDF
[Arxiv] PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions
[Arxiv] Self-supervised Single-view 3D Reconstruction via Semantic Consistency
[Arxiv] Convolutional Occupancy Networks
[Arxiv] Meta3D: Single-View 3D Object Reconstruction from Shape Priors in Memory
[Arxiv] STD-Net: Structure-preserving and Topology-adaptive Deformation Network for 3D Reconstruction from a Single Image
[Arxiv] Curvature Regularized Surface Reconstruction from Point Cloud
[Arxiv] Hypernetwork approach to generating point clouds
[Arxiv] Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data
[Arxiv] Meshlet Priors for 3D Mesh Reconstruction
[Arxiv] Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction
[Arxiv] SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization
[CVPR2019] Occupancy Networks: Learning 3D Reconstruction in Function Space [pytorch] 🔥⭐
[NeurIPS2019] DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction [tensorflow]
[NeurIPS2019] Learning to Infer Implicit Surfaces without 3D Supervision
[CVPR2019] A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images [pytorch & tensorflow]
[Arxiv] Deep Level Sets: Implicit Surface Representations for 3D Shape Inference
[CVPR2019] Learning Implicit Fields for Generative Shape Modeling [tensorflow] 🔥
[ICCV2019] Point-based Multi-view Stereo Network [pytorch] ⭐
[Arxiv] TSRNet: Scalable 3D Surface Reconstruction Network for Point Clouds using Tangent Convolution
[Arxiv] DR-KFD: A Differentiable Visual Metric for 3D Shape Reconstruction
[ICCV2019] GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion
[ICCV2019] Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation [pytorch]
[ICCV2019] Few-Shot Generalization for Single-Image 3D Reconstruction via Priors
[ICCV2019] Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks
[AAAI2018] Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction [tensorflow] ⭐🔥
[NeurIPS2017] MarrNet: 3D Shape Reconstruction via 2.5D Sketches [torch]:star::fire:

3D Scene Understanding

[CVPR2020] Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions
[Arxiv] LayoutMP3D: Layout Annotation of Matterport3D
[CVPR2020] Local Implicit Grid Representations for 3D Scenes
[Arxiv] Scan2Plan: Efficient Floorplan Generation from 3D Scans of Indoor Scenes
[CVPR2020] RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds [tensorflow] ::fire::
[CVPR2020] Intelligent Home 3D: Automatic 3D-House Design from Linguistic Descriptions Only
[ICRA2020] 3DCFS: Fast and Robust Joint 3D Semantic-Instance Segmentation via Coupled Feature Selection
[Arxiv] Indoor Scene Recognition in 3D
[Journal] Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense
[Arxiv] BlockGAN Learning 3D Object-aware Scene Representations from Unlabelled Images
[Arxiv] 3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans
[Arxiv] Generating 3D People in Scenes without People
[CVPR2019] Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments
[ICCV2019] Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense
[ICCV2019] U4D: Unsupervised 4D Dynamic Scene Understanding
[ICCV2019] UprightNet: Geometry-Aware Camera Orientation Estimation from Single Images
[ICCV2019] Habitat: A Platform for Embodied AI Research [habitat-api] [habitat-sim] ⭐
[ICCV2019] SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences [project page] ⭐
[ICCV2019] Neural Inverse Rendering of an Indoor Scene From a Single Image
[ICCV2019] SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation [pytorch]
[ICCV2019] RIO: 3D Object Instance Re-Localization in Changing Indoor Environments [dataset]
[ICCV2019] CamNet: Coarse-to-Fine Retrieval for Camera Re-Localization
[ICCV2019] U4D: Unsupervised 4D Dynamic Scene Understanding
[NeurIPS2018] Learning to Exploit Stability for 3D Scene Parsing

3D Scene Reconstruction

[CVPR2020] DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
[Arxiv] SceneCAD: Predicting Object Alignments and Layouts in RGB-D Scans
[Arxiv] Removing Dynamic Objects for Static Scene Reconstruction using Light Fields
[Arxiv] Atlas: End-to-End 3D Scene Reconstruction from Posed Images
[Arxiv] Scan2Plan: Efficient Floorplan Generation from 3D Scans of Indoor Scenes
[Arxiv] Plane Pair Matching for Efficient 3D View Registration
[CVPR2020] Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image
[Arxiv] Indoor Layout Estimation by 2D LiDAR and Camera Fusion
[Arxiv] General 3D Room Layout from a Single View by Render-and-Compare
[ICCV2019] Learning to Reconstruct 3D Manhattan Wireframes from a Single Image [pytorch]
[CVPR2019] PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image [pytorch]:fire:
[CVPR2018] Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene [pytorch]
[ICCV2019] 3D Scene Reconstruction with Multi-layer Depth and Epipolar Transformers
[ICCV Workshop2019] Silhouette-Assisted 3D Object Instance Reconstruction from a Cluttered Scene
[ICCV2019] 3D-RelNet: Joint Object and Relation Network for 3D prediction [pytorch]
[3DV2019] Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Network
[CVPR2018] Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene [pytorch]
[IROS2017] Indoor Scan2BIM: Building Information Models of House Interiors

General Methods

[Arxiv] Joint Supervised and Self-Supervised Learning for 3D Real-World Challenges
[Arxiv] LIGHTCONVPOINT: CONVOLUTION FOR POINTS [pytorch]
[Arxiv] Variational Auto-Decoder [pytorch]
[Arxiv] Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification
[CVPR2020] DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes [pytorch]
[CVPR2020] RPM-Net: Robust Point Matching using Learned Features [github]
[CVPR2020] Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds
[CVPR2020] PointGMM: a Neural GMM Network for Point Clouds
[Arxiv] Dynamic ReLU
[CVPR2020] SampleNet: Differentiable Point Cloud Sampling [pytorch]
[Arxiv] Defense-PointNet: Protecting PointNet Against Adversarial Attacks
[CVPR2020] FPConv: Learning Local Flattening for Point Convolution [pytorch]
[ICCV2019] PU-GAN: a Point Cloud Upsampling Adversarial Network:fire:
[CVPR2019] Relation-Shape Convolutional Neural Network for Point Cloud Analysis [pytorch] 🔥
[CVPR2018] PU-Net: Point Cloud Upsampling Network ⭐🔥
[Arxiv] PointAugment: an Auto-Augmentation Framework for Point Cloud Classification
[ICLR2017] DEEP LEARNING WITH SETS AND POINT CLOUDS
[NeurIPS2017] Deep Sets
[Siggraph2006] Designing with Distance Fields

Others (inc. Networks in Classification, Matching, Registration, Alignment, Depth, Pose, Keypoints, etc.)

[CVPR2020] Towards Better Generalization: Joint Depth-Pose Learning without PoseNet [pytorch]
[Arxiv] Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences
[Arxiv] Adversarial Texture Optimization from RGB-D Scans
[Arxiv] SAPIEN: A SimulAted Part-based Interactive ENvironment
[CVPR2020] G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features
[Arxiv] On Localizing a Camera from a Single Image
[Arxiv] DeepFit: 3D Surface Fitting via Neural Network Weighted Least Squares
[CVPR2020] KFNet: Learning Temporal Camera Relocalization using Kalman Filtering
[Arxiv] Neural Contours: Learning to Draw Lines from 3D Shapes
[Arxiv] 3dDepthNet: Point Cloud Guided Depth Completion Network for Sparse Depth and Single Color Image
[Arxiv] Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets
[CVPR2020] End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
[Arxiv] PnP-Net: A hybrid Perspective-n-Point Network
[CVPR2020] MobilePose: Real-Time Pose Estimation for Unseen Objects with Weak Shape Supervision
[CVPR2020] D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
[ICIP2020] TRIANGLE-NET: TOWARDS ROBUSTNESS IN POINT CLOUD CLASSIFICATION
[ICRA2020] Robust 6D Object Pose Estimation by Learning RGB-D Features
[Arxiv] Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fields
[Arxiv] Learning multiview 3D point cloud registration [code]
[Arxiv] Single Image Depth Estimation Trained via Depth from Defocus Cues [pytorch]
[Arxiv] DepthTransfer: Depth Extraction from Video Using Non-parametric Sampling
[Arxiv] Target-less registration of point clouds: A review
[Arxiv] Quaternion Equivariant Capsule Networks for 3D point clouds
[Arxiv] Category-Level Articulated Object Pose Estimation
[Arxiv] A Quantum Computational Approach to Correspondence Problems on Point Sets
[Arxiv] DeepSFM: Structure From Motion Via Deep Bundle Adjustment
[Arxiv] P²GNet: Pose-Guided Point Cloud Generating Networks for 6-DoF Object Pose Estimation
[ICCV2019] Learning Local RGB-to-CAD Correspondences for Object Pose Estimation
[ICCV2019] Joint Embedding of 3D Scan and CAD Objects [dataset]
[ICLR2019] BA-NET: DENSE BUNDLE ADJUSTMENT NETWORKS [tensorflow]
[ICCV2019] GP²C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wild
[ICCV2019] Closed-Form Optimal Two-View Triangulation Based on Angular Errors
[ICCV2019] Polarimetric Relative Pose Estimation
[ICCV2019] End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans
[ICCV2019] Deep Non-Rigid Structure from Motion
[CVPR2019] On the Continuity of Rotation Representations in Neural Networks [pytorch]
[Arxiv] Deep Interpretable Non-Rigid Structure from Motion [tensorflow]
[Arxiv] IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks [dataset]
[CVPR2019] Scan2CAD: Learning CAD Model Alignment in RGB-D Scans [pytorch] 🔥
[3DV2019] Location Field Descriptors: Single Image 3D Model Retrieval in the Wild
[CVPR2016] Marr Revisited: 2D-3D Alignment via Surface Normal Prediction [caffe]

Survey, Resources and Tools

[CVPR2020] RoboTHOR: An Open Simulation-to-Real Embodied AI Platform [Project page]
[EG2020] State of the Art on Neural Rendering
[IJCAI-PRICAI2020] 3D-FUTURE: 3D FUrniture shape with TextURE
[Arxiv] Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways
[Arxiv] KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations
[Arxiv] A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
[Arxiv] From Seeing to Moving: A Survey on Learning for Visual Indoor Navigation (VIN)
[Arxiv] DIODE: A Dense Indoor and Outdoor DEpth Dataset [dataset]
[Github] Various GANs with Pytorch.
[Arxiv] SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances [dataset]
[CVM] A Survey on Deep Geometry Learning: From a Representation Perspective
[Arxiv] A survey on Semi-, Self- and Unsupervised Techniques in Image Classification
[Arxiv] fastai: A Layered API for Deep Learning
[Arxiv] AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance [dataset]
[Arxiv] VIRTUAL KITTI 2 [dataset]
[Arxiv] Tutorial on Variational Autoencoders
[Arxiv] Review: deep learning on 3D point clouds
[Arxiv] Image Segmentation Using Deep Learning: A Survey
[CVPR2018] Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction
[Arxiv] Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey
[Arxiv] MCMLSD: A Probabilistic Algorithm and Evaluation Framework for Line Segment Detection
[Arxiv] Deep Learning for 3D Point Clouds: A Survey
[Arxiv] A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images
[Arxiv] A Survey on Deep Learning Architectures for Image-based Depth Reconstruction
[Arxiv] secml: A Python Library for Secure and Explainable Machine Learning
[Arxiv] Bundle Adjustment Revisited
[ICCV2019] Deep CG2Real: Synthetic-to-Real Translation via Image Disentanglement
[Arxiv] SIFT Meets CNN: A Decade Survey of Instance Retrieval
[ICCV2019] Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data [tensorflow]
[Arxiv] BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks [dataset]
[Arxiv] Imbalance Problems in Object Detection: A Review [repository]
[IJCV] Deep Learning for Generic Object Detection: A Survey
[Arxiv] Differentiable Visual Computing (Ph.D thesis)
[BMVC2018] InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset [dataset]
[ICCV2017] The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes [dataset] [script] ⭐
[Arxiv] SynthCity: A large scale synthetic point cloud [dataset]
[Github] Mesh Voxelization (SDFs or Occupancy grids)
[Github] SDFGen (to generate grid-based signed distance field (level set))
[Github] Blender renderer for python
[Github] Blender renderer for python
[Github] Volumetric TSDF Fusion of RGB-D Images in Python
[Github] Volumetric TSDF Fusion of Multiple Depth Maps
[Github] PyFusion
[Github] PyRender
[Github] PyMCubes
[Github] Watertight and Simplified Meshes through TSDF Fusion (Python tool for obtaining watertight meshes using TSDF fusion.)
[Github] Several tools about SDF functions.
[Github] 3DMatch Toolbox
[stackoverflow] Computing truncated signed distance function(TSDF) from a point cloud
[Github] voxblox: A library for flexible voxel-based mapping, mainly focusing on truncated and Euclidean signed distance fields.
[Github] Discregrid: A static C++ library for the generation of discrete functions on a box-shaped domain. This is especially suited for the generation of signed distance fields.
[Github] awesome-voxel: Voxel resources for coders
[Github] gvdb-voxels: Sparse volume compute and rendering on NVIDIA GPUs
[Github] pyntcloud is a Python library for working with 3D point clouds.
[Github] Open3D: A Modern Library for 3D Data Processing
[Github] mesh_to_sdf: Calculate signed distance fields for arbitrary meshes

vincenthesiyuan / 3D-Shape-Analysis-Paper-List