8 citations · 20 across the 25 of their papers we have counts for
10 papers · 1 filter
X-Prompt: Multi-modal Visual Prompt for Video Object Segmentation
Pinxue Guo, Wanyun Li, Hao Huang +7
Multi-modal Video Object Segmentation (VOS), including RGB-Thermal, RGB-Depth, and RGB-Event, has garnered attention due to its capability to address challenging scenarios where tr…
LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation
Henghui Ding, Lingyi Hong, Chang Liu +30
Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th…
General Compression Framework for Efficient Transformer Object Tracking
Lingyi Hong, Jinglun Li, Xinyu Zhou +10
Previous works have attempted to improve tracking efficiency through lightweight architecture design or knowledge distillation from teacher models to compact student trackers. Howe…
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…
Improving Adversarial Transferability with Neighbourhood Gradient Information
Haijing Guo, Jiafeng Wang, Zhaoyu Chen +5
Deep neural networks (DNNs) are known to be susceptible to adversarial examples, leading to significant performance degradation. In black-box attack scenarios, a considerable attac…
LVOS: A Benchmark for Large-scale Long-term Video Object Segmentation
Lingyi Hong, Zhongying Liu, Wenchao Chen +9
Video object segmentation (VOS) aims to distinguish and track target objects in a video. Despite the excellent performance achieved by off-the-shell VOS models, existing VOS benchm…
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…
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…
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…
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…