1 citations · 1 across the 4 of their papers we have counts for
4 papers
Frame Order Matters: A Temporal Sequence-Aware Model for Few-Shot Action Recognition
Bozheng Li, Mushui Liu, Gaoang Wang +1
In this paper, we propose a novel Temporal Sequence-Aware Model (TSAM) for few-shot action recognition (FSAR), which incorporates a sequential perceiver adapter into the pre-traini…
OmniCLIP: Adapting CLIP for Video Recognition with Spatial-Temporal Omni-Scale Feature Learning
Mushui Liu, Bozheng Li, Yunlong Yu
Recent Vision-Language Models (VLMs) \textit{e.g.} CLIP have made great progress in video recognition. Despite the improvement brought by the strong visual backbone in extracting s…
Dense Affinity Matching for Few-Shot Segmentation
Hao Chen, Yonghan Dong, Zheming Lu +4
Few-Shot Segmentation (FSS) aims to segment the novel class images with a few annotated samples. In this paper, we propose a dense affinity matching (DAM) framework to exploit the…
DenseDINO: Boosting Dense Self-Supervised Learning with Token-Based Point-Level Consistency
Yike Yuan, Xinghe Fu, Yunlong Yu +1
In this paper, we propose a simple yet effective transformer framework for self-supervised learning called DenseDINO to learn dense visual representations. To exploit the spatial i…