285 citations · 499 across the 33 of their papers we have counts for
8 papers · 1 filter
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +4
Recently, large-scale pre-trained language-image models like CLIP have shown extraordinary capabilities for understanding spatial contents, but naively transferring such models to…
Towards Real-World Visual Tracking with Temporal Contexts
Ziang Cao, Ziyuan Huang, Liang Pan +3
Visual tracking has made significant improvements in the past few decades. Most existing state-of-the-art trackers 1) merely aim for performance in ideal conditions while overlooki…
Temporally-Adaptive Models for Efficient Video Understanding
Ziyuan Huang, Shiwei Zhang, Liang Pan +4
Spatial convolutions are extensively used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in diffe…
VideoComposer: Compositional Video Synthesis with Motion Controllability
Xiang Wang, Hangjie Yuan, Shiwei Zhang +6
The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis. However, achieving controllable vide…
MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Zhiwu Qing +4
Current state-of-the-art approaches for few-shot action recognition achieve promising performance by conducting frame-level matching on learned visual features. However, they gener…
Enlarging Instance-specific and Class-specific Information for Open-set Action Recognition
Jun Cen, Shiwei Zhang, Xiang Wang +4
Open-set action recognition is to reject unknown human action cases which are out of the distribution of the training set. Existing methods mainly focus on learning better uncertai…
CLIP-guided Prototype Modulating for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Jun Cen +4
Learning from large-scale contrastive language-image pre-training like CLIP has shown remarkable success in a wide range of downstream tasks recently, but it is still under-explore…
HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Zhiwu Qing +4
Recent attempts mainly focus on learning deep representations for each video individually under the episodic meta-learning regime and then performing temporal alignment to match qu…