I'll use the following icons to differentiate 3D representations:
- 📷 Multi-view Images
- 👾 Volumetric
- 🎲 Point Cloud
- 💎 Polygonal Mesh
- 💊 Primitive-based
Category-Specific Object Reconstruction from a Single Image (2014) [Paper]
Viewpoints and Keypoints (2015) [Paper]
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views (2015 ICCV) [Paper]
PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization (2015) [Paper]
Modeling Uncertainty in Deep Learning for Camera Relocalization (2016) [Paper]
Robust camera pose estimation by viewpoint classification using deep learning (2016) [Paper]
Geometric loss functions for camera pose regression with deep learning (2017 CVPR) [Paper]
Generic 3D Representation via Pose Estimation and Matching (2017) [Paper]
3D Bounding Box Estimation Using Deep Learning and Geometry (2017) [Paper]
6-DoF Object Pose from Semantic Keypoints (2017) [Paper]
Relative Camera Pose Estimation Using Convolutional Neural Networks (2017) [Paper]
3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions (2017) [Paper]
Single Image 3D Interpreter Network (2016) [Paper] [Code]
Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction (2018 CVPR) [Paper]
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes (2018) [Paper]
Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images (2018 CVPR) [Paper]
Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling (2018 CVPR) [Paper]
3D Pose Estimation and 3D Model Retrieval for Objects in the Wild (2018 CVPR) [Paper]
