4 citations · 7 across the 7 of their papers we have counts for
8 papers
ReSight-SMC: Two-Stage Power Sampling via Island SMC with Visual Scouts
Yaowen Zhang, Xiangyu Qiu, Junyi Hu +5
Power sampling has emerged as a training-free approach to LLM reasoning, eliciting capabilities comparable to reinforcement learning by sharpening the model distribution over compl…
Scaling Representation Diversity: Modulated Attention and Reconstructive Regularization for Visual Grounding
Junyi Hu, Tian Bai, Fengyi Wu +7
Referring Expression Comprehension (REC) is commonly studied under dataset-specific fine-tuning, resulting in specialist models with limited cross-dataset generalization. In this w…
LCPNet: Latent Consistent Proximal Unfolding Network for Infrared Small Target Detection
Tianfang Zhang, Lei Li, Chang Liu +3
Infrared small target detection (IRSTD) aims to identify long distance small targets from complex infrared backgrounds, and is a fundamental task in remote sensing. Deep learning m…
ExpAlign: Expectation-Guided Vision-Language Alignment for Open-Vocabulary Grounding
Junyi Hu, Tian Bai, Fengyi Wu +3
Open-vocabulary grounding requires accurate vision-language alignment under weak supervision, yet existing methods either rely on global sentence embeddings that lack fine-grained…
RPCANet++: Deep Interpretable Robust PCA for Sparse Object Segmentation
Fengyi Wu, Yimian Dai, Tianfang Zhang +4
Robust principal component analysis (RPCA) decomposes an observation matrix into low-rank background and sparse object components. This capability has enabled its application in ta…
PHCT: Plug-and-Play Hierarchical C2F Transformer for Multi-Scale Feature Fusion
Junyi Hu, Tian Bai, Fengyi Wu +2
Feature fusion plays a pivotal role in achieving high performance in vision models, yet existing attention-based fusion techniques often suffer from substantial computational overh…
Neural Spatial-Temporal Tensor Representation for Infrared Small Target Detection
Fengyi Wu, Simin Liu, Haoan Wang +3
Optimization-based approaches dominate infrared small target detection as they leverage infrared imagery's intrinsic low-rankness and sparsity. While effective for single-frame ima…
RPCANet: Deep Unfolding RPCA Based Infrared Small Target Detection
Fengyi Wu, Tianfang Zhang, Lei Li +2
Deep learning (DL) networks have achieved remarkable performance in infrared small target detection (ISTD). However, these structures exhibit a deficiency in interpretability and a…