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Name: HUST Vision Lab

Type: Organization

Bio: HUST Vision Lab of the School of EIC in HUST. Lab Lead @xinggangw

Location: Wuhan, China

HUST Vision Lab's Projects

sparseinst icon sparseinst

[CVPR 2022] SparseInst: Sparse Instance Activation for Real-Time Instance Segmentation

sparsetrack icon sparsetrack

Official PyTorch implementation of SparseTrack (the new version of code will come soon)

stableptq icon stableptq

Stabilized Activation Scale Estimation for Precise Post-Training Quantization

symphonies icon symphonies

[CVPR 2024] Symphonies (Scene-from-Insts): Symphonize 3D Semantic Scene Completion with Contextual Instance Queries

tevit icon tevit

Temporally Efficient Vision Transformer for Video Instance Segmentation, CVPR 2022, Oral

tineuvox icon tineuvox

TiNeuVox: Fast Dynamic Radiance Fields with Time-Aware Neural Voxels (SIGGRAPH Asia 2022)

topformer icon topformer

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation, CVPR2022

vad icon vad

[ICCV 2023] VAD: Vectorized Scene Representation for Efficient Autonomous Driving

vim icon vim

Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

vitmatte icon vitmatte

[Information Fusion] Boosting Image Matting with Pretrained Plain Vision Transformers

vma icon vma

A general map auto annotation framework based on MapTR, with high flexibility in terms of spatial scale and element type

weaksam icon weaksam

WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition

weaktr icon weaktr

WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation

yolop icon yolop

You Only Look Once for Panopitic Driving Perception.(MIR2022)

yolos icon yolos

[NeurIPS 2021] You Only Look at One Sequence

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