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

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Hierarchical Visual Categories Modeling: A Joint Representation Learning and Density Estimation Framework for Out-of-Distribution Detection

Jinglun Li, Xinyu Zhou, Pinxue Guo +4

Detecting out-of-distribution inputs for visual recognition models has become critical in safe deep learning. This paper proposes a novel hierarchical visual category modeling sche…

cs.CV2024

TagOOD: A Novel Approach to Out-of-Distribution Detection via Vision-Language Representations and Class Center Learning

Jinglun Li, Xinyu Zhou, Kaixun Jiang +5

Multimodal fusion, leveraging data like vision and language, is rapidly gaining traction. This enriched data representation improves performance across various tasks. Existing meth…

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

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…