DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERINGUNIVERSITY OF CALIFORNIA, SAN DIEGO
CSE291-J00: Deep Learning Lab (Computer Vision)
Paper Reading List
Long-tailed Detectection
Papers to compare
- Focal Loss for Dense Object Detection
- Equalization Loss for Long-Tailed Object Recognition (LVIS 2019 champion)
- Decoupling Representation and Classifier for Long-Tailed Recognition (LVIS 2020 baseline)
- Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
- Learning to Segment the Tail
- 1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask
At least 5 papers should be compared. You can choose one of colored papers.
Reference
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- Mask R-CNN
- Feature Pyramid Networks for Object Detection
- LVIS: A Dataset for Large Vocabulary Instance Segmentation
Instance Segmentation
Papers to compare
- SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
- GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud
- Associatively Segmenting Instances and Semantics in Point Clouds
- 3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation
- PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Reference
- PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
- 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
- Deep Hough Voting for 3D Object Detection in Point Clouds
- H3DNet: 3D Object Detection Using Hybrid Geometric Primitives
- Generative Sparse Detection Networks for 3D Single-shot Object Detection
Part Segmentation
Papers to compare
- PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding (baseline)
- Learning object bounding boxes for 3d instance segmentation on point clouds
- SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
- GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud
- Point Cloud Instance Segmentation using Probabilistic Embeddings
Reference
The same as Instance Segmentation.
Tracking
Papers to compare
- Scalability in Perception for Autonomous Driving: Waymo Open Dataset
- 3D Multi-Object Tracking: A Baseline and New Evaluation Metrics
- 1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking (1st place)
- PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection (2nd place)
Reference
- Multiple Object Tracking: A Literature Review
- Simple Online and Realtime Tracking
- Simple Online and Realtime Tracking with a Deep Association Metric