activity
20162024
most citedMulti-Attention Network for Compressed Video Referring Object Segmentation

2 citations · 3 across the 8 of their papers we have counts for

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8 papers · 1 filter

cs.CV2024

ClickTrack: Towards Real-time Interactive Single Object Tracking

Kuiran Wang, Xuehui Yu, Wenwen Yu +5

Single object tracking(SOT) relies on precise object bounding box initialization. In this paper, we reconsidered the deficiencies in the current approaches to initializing single o…

cs.CV2024

ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts

Xumeng Han, Longhui Wei, Zhiyang Dou +6

Mixture-of-Experts (MoE) models embody the divide-and-conquer concept and are a promising approach for increasing model capacity, demonstrating excellent scalability across multipl…

cs.CV2024

CPR++: Object Localization via Single Coarse Point Supervision

Xuehui Yu, Pengfei Chen, Kuiran Wang +5

Point-based object localization (POL), which pursues high-performance object sensing under low-cost data annotation, has attracted increased attention. However, the point annotatio…

cs.CV2024

P2Seg: Pointly-supervised Segmentation via Mutual Distillation

Zipeng Wang, Xuehui Yu, Xumeng Han +4

Point-level Supervised Instance Segmentation (PSIS) aims to enhance the applicability and scalability of instance segmentation by utilizing low-cost yet instance-informative annota…

cs.CV2023

Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes

Di Wu, Pengfei Chen, Xuehui Yu +3

Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low ann…

cs.CV20222 cited

Multi-Attention Network for Compressed Video Referring Object Segmentation

Weidong Chen, Dexiang Hong, Yuankai Qi +5

Referring video object segmentation aims to segment the object referred by a given language expression. Existing works typically require compressed video bitstream to be decoded to…