5 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection
Jinglun Li, Kaixun Jiang, Zhaoyu Chen +4
Pre-trained vision-language models have exhibited remarkable abilities in detecting out-of-distribution (OOD) samples. However, some challenging OOD samples, which lie close to in-…
Enhancing Environmental Robustness in Few-shot Learning via Conditional Representation Learning
Qianyu Guo, Jingrong Wu, Tianxing Wu +3
Few-shot learning (FSL) has recently been extensively utilized to overcome the scarcity of training data in domain-specific visual recognition. In real-world scenarios, environment…
Boosting Salient Object Detection with Knowledge Distillated from Large Foundation Models
Miaoyang He, Shuyong Gao, Tsui Qin Mok +2
Salient Object Detection (SOD) aims to identify and segment prominent regions within a scene. Traditional models rely on manually annotated pseudo labels with precise pixel-level a…
DeTrack: In-model Latent Denoising Learning for Visual Object Tracking
Xinyu Zhou, Jinglun Li, Lingyi Hong +4
Previous visual object tracking methods employ image-feature regression models or coordinate autoregression models for bounding box prediction. Image-feature regression methods hea…