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20232026
most citedExploring Dynamic Transformer for Efficient Object Tracking

17 citations · 25 across the 16 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

SUTrack: Towards Simple and Unified Single Object Tracking

Xin Chen, Ben Kang, Wanting Geng +4

In this paper, we propose a simple yet unified single object tracking (SOT) framework, dubbed SUTrack. It consolidates five SOT tasks (RGB-based, RGB-Depth, RGB-Thermal, RGB-Event,…

cs.CV2024★ 5 cited

Underwater Object Detection in the Era of Artificial Intelligence: Current, Challenge, and Future

Long Chen, Yuzhi Huang, Junyu Dong +5

Underwater object detection (UOD), aiming to identify and localise the objects in underwater images or videos, presents significant challenges due to the optical distortion, water…

cs.CV2024

MambaVT: Spatio-Temporal Contextual Modeling for robust RGB-T Tracking

Simiao Lai, Chang Liu, Jiawen Zhu +4

Existing RGB-T tracking algorithms have made remarkable progress by leveraging the global interaction capability and extensive pre-trained models of the Transformer architecture. N…

cs.CV2024

EvSign: Sign Language Recognition and Translation with Streaming Events

Pengyu Zhang, Hao Yin, Zeren Wang +5

Sign language is one of the most effective communication tools for people with hearing difficulties. Most existing works focus on improving the performance of sign language tasks o…

cs.CV2024★ 17 cited

Exploring Dynamic Transformer for Efficient Object Tracking

Jiawen Zhu, Xin Chen, Haiwen Diao +6

The speed-precision trade-off is a critical problem for visual object tracking which usually requires low latency and deployment on constrained resources. Existing solutions for ef…

cs.CV2024★ 3 cited

Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters

Jiazuo Yu, Yunzhi Zhuge, Lu Zhang +4

Continual learning can empower vision-language models to continuously acquire new knowledge, without the need for access to the entire historical dataset. However, mitigating the p…