Papers and Benchmarks about semantic segmentation, instance segmentation, panoptic segmentation and video segmentation
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。
A curated list of Multimodal Related Research.
Paper bank for Self-Supervised Learning
CenterMask2 on top of detectron2, in CVPR 2020
Deep learning for video compression.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Image augmentation for machine learning experiments.
Multi-object image datasets with ground-truth segmentation masks and generative factors.
A high performance object detection and face detection toolkit based on PaddlePaddle.
A high performance semantic segmentation toolkit based on PaddlePaddle. (『飞桨』图像分割库）
:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version
PyTorch implementation of Contrastive Learning methods; List of awesome-contrastive-learning papers
novel deep learning research works with PaddlePaddle
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Examples of using sparse attention, as in "Generating Long Sequences with Sparse Transformers"
[NeurIPS-2020] Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID.
A PyTorch-Based Framework for Deep Learning in Computer Vision
A paper list of some recent Transformer-based CV works.