100 citations · 140 across the 6 of their papers we have counts for
7 papers
From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health
He Hu, Yucheng Zhou, Qianning Wang +8
The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, high cost, stigma, and privacy c…
PSLT: A Light-weight Vision Transformer with Ladder Self-Attention and Progressive Shift
Gaojie Wu, Wei-Shi Zheng, Yutong Lu +1
Vision Transformer (ViT) has shown great potential for various visual tasks due to its ability to model long-range dependency. However, ViT requires a large amount of computing res…
Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry
Yawen Cui, Zitong Yu, Wei Peng +1
Few-Shot Class-Incremental Learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by avoiding the overfitting and catastrophic forgetting simultan…
Towards Generalizable Person Re-identification with a Bi-stream Generative Model
Xin Xu, Wei Liu, Zheng Wang +2
Generalizable person re-identification (re-ID) has attracted growing attention due to its powerful adaptation capability in the unseen data domain. However, existing solutions ofte…
Semantic-guided Pixel Sampling for Cloth-Changing Person Re-identification
Xiujun Shu, Ge Li, Xiao Wang +2
Cloth-changing person re-identification (re-ID) is a new rising research topic that aims at retrieving pedestrians whose clothes are changed. This task is quite challenging and has…
An End-to-End Foreground-Aware Network for Person Re-Identification
Yiheng Liu, Wengang Zhou, Jianzhuang Liu +3
Person re-identification is a crucial task of identifying pedestrians of interest across multiple surveillance camera views. In person re-identification, a pedestrian is usually re…
Effective Image Retrieval via Multilinear Multi-index Fusion
Zhizhong Zhang, Yuan Xie, Wensheng Zhang +1
Multi-index fusion has demonstrated impressive performances in retrieval task by integrating different visual representations in a unified framework. However, previous works mainly…