deeplearning-pwcn
github.com/gojay001/deeplearning-pwcn ↗There are paper with code for CV / AIGC / LLM / VLM.
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me multiple object tracking resources from deeplearning-pwcn"
Installation instructions →What's inside
Few-Shot Segmentation
- CANet
CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning
- co-FCN
Conditional Networks for Few-Shot Semantic Segmentation
- CRNet
CRNet: Cross-Reference Networks for Few-Shot Segmentation
- LTM
A New Local Transformation Module for Few-Shot Segmentation
- OSLSM
One-Shot Learning for Semantic Segmentation
- PGNet
Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic Segmentation
Object Tracking
- DeepSORTMultiple Object Tracking
Simple Online and Realtime Tracking with a Deep Association Metric
- FairMOTMultiple Object Tracking
A Simple Baseline for Multi-Object Tracking
- FFTMultiple Object Tracking
Multiple Object Tracking by Flowing and Fusing
- GlobalTrackVisual Object Tracking
GlobalTrack: A Simple and Strong Baseline for Long-term Tracking
- JRMOTMultiple Object Tracking
JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset
- PAMCC-AOTVisual Object Tracking
Pose-Assisted Multi-Camera Collaboration for Active Object Tracking
Object Detection
- Faster R-CNN
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Survey
- FSL-Survey-2019
Generalizing from a Few Examples: A Survey on Few-Shot Learning
Backbone
Vision Transformer
- Image Transformer
Image Transformer
Object Segmentation
- Mask R-CNN
Mask R-CNN
3D Object Detection
- PV-RCNN
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Showing a sample of 29 resources. View the full list on GitHub →