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[ICCV'21] Learning Spatio-Temporal Transformer for Visual Tracking
The main features of researchmm/stark are: Video Understanding and Tracking.
Projects with overlapping indexed features include: anirudh257/strm — [CVPR 2022] Official Pytorch Implementation for "Spatio-temporal Relation Modeling for Few-shot Action Recognition".… botaoye/ostrack — [ECCV 2022] Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework. chenxin-dlut/transt — Transformer Tracking (CVPR2021). little-podi/aiatrack — [ECCV'22] The official PyTorch implementation of our ECCV 2022 paper: "AiATrack: Attention in Attention for… masterbin-iiau/unicorn — [ECCV'22 Oral] Towards Grand Unification of Object Tracking. mcg-nju/videomae — [NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video…
ECCV 2022 Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
ECCV'22 The official PyTorch implementation of our ECCV 2022 paper: "AiATrack: Attention in Attention for Transformer Visual Tracking".
CVPR 2022 Official Pytorch Implementation for "Spatio-temporal Relation Modeling for Few-shot Action Recognition". SOTA Results for Few-shot Action Recognition
