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Found 5 papers, 0 papers with code
LVOS: A Benchmark for Large-scale Long-term Video Object Segmentation
Video object segmentation (VOS) aims to distinguish and track target objects in a video.
OneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuning
To evaluate the effectiveness of our general framework OneTracker, which is consisted of Foundation Tracker and Prompt Tracker, we conduct extensive experiments on 6 popular tracking tasks across 11 benchmarks and our OneTracker outperforms other models and achieves state-of-the-art performance.
ClickVOS: Click Video Object Segmentation
To address these limitations, we propose the setting named Click Video Object Segmentation (ClickVOS) which segments objects of interest across the whole video according to a single click per object in the first frame.
Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
Therefore, using all features in the template and memory can lead to redundancy and impair tracking performance.
Hierarchical Visual Categories Modeling: A Joint Representation Learning and Density Estimation Framework for Out-of-Distribution Detection
We use one fold as the in-distribution dataset and the others as out-of-distribution datasets to evaluate the proposed method.
