Pinned Repositories
hydra
Official implementation of "Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers"
GenVIS
[CVPR'23] A Generalized Framework for Video Instance Segmentation
apex
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
IFC
Video Instance Segmentation using Inter-Frame Communication Transformers (NeurIPS 2021)
netadapt
This repo contains the official Pytorch reimplementation of the paper "NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications".
set_classifier
Official PyTorch implementation of: "Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos" (CVPR 2022)
triton_flashattn
VITA
VITA: Video Instance Segmentation via Object Token Association (NeurIPS 2022)
sukjunhwang's Repositories
sukjunhwang/VITA
VITA: Video Instance Segmentation via Object Token Association (NeurIPS 2022)
sukjunhwang/IFC
Video Instance Segmentation using Inter-Frame Communication Transformers (NeurIPS 2021)
sukjunhwang/set_classifier
Official PyTorch implementation of: "Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos" (CVPR 2022)
sukjunhwang/triton_flashattn
sukjunhwang/netadapt
This repo contains the official Pytorch reimplementation of the paper "NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications".
sukjunhwang/apex
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
sukjunhwang/ClassyVision
An end-to-end PyTorch framework for image and video classification
sukjunhwang/cocoapi
COCO API Customized for YouTubeVIS evaluation
sukjunhwang/detectron2
Detectron2 is FAIR's next-generation research platform for object detection and segmentation.
sukjunhwang/imgclsmob
Sandbox for training convolutional networks for computer vision
sukjunhwang/MaskTrackRCNN
MaskTrackRCNN for video instance segmentation based on mmdetection
sukjunhwang/s4
Structured state space sequence models
sukjunhwang/tao
Code for downloading and using the TAO dataset: http://taodataset.org/
sukjunhwang/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.