5 citations · 5 across the 7 of their papers we have counts for
7 papers
Adaptive Attention Distillation for Robust Few-Shot Segmentation under Environmental Perturbations
Qianyu Guo, Jingrong Wu, Jieji Ren +2
Few-shot segmentation (FSS) aims to rapidly learn novel class concepts from limited examples to segment specific targets in unseen images, and has been widely applied in areas such…
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…
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…
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…