most citedReading Relevant Feature from Global Representation Memory for Visual Object Tracking

5 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20243 cited

OneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuning

Lingyi Hong, Shilin Yan, Renrui Zhang +8

Visual object tracking aims to localize the target object of each frame based on its initial appearance in the first frame. Depending on the input modility, tracking tasks can be d…

cs.CV2024

OneVOS: Unifying Video Object Segmentation with All-in-One Transformer Framework

Wanyun Li, Pinxue Guo, Xinyu Zhou +5

Contemporary Video Object Segmentation (VOS) approaches typically consist stages of feature extraction, matching, memory management, and multiple objects aggregation. Recent advanc…

cs.CV2024

ClickVOS: Click Video Object Segmentation

Pinxue Guo, Lingyi Hong, Xinyu Zhou +7

Video Object Segmentation (VOS) task aims to segment objects in videos. However, previous settings either require time-consuming manual masks of target objects at the first frame d…

cs.CV20245 cited

Reading Relevant Feature from Global Representation Memory for Visual Object Tracking

Xinyu Zhou, Pinxue Guo, Lingyi Hong +4

Reference features from a template or historical frames are crucial for visual object tracking. Prior works utilize all features from a fixed template or memory for visual object t…

cs.LG20241 cited

AlphaRank: An Artificial Intelligence Approach for Ranking and Selection Problems

Ruihan Zhou, L. Jeff Hong, Yijie Peng

We introduce AlphaRank, an artificial intelligence approach to address the fixed-budget ranking and selection (R&S) problems. We formulate the sequential sampling decision as a Mar…