116 citations · 225 across the 27 of their papers we have counts for
9 papers · 1 filter
Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval
Haochen Han, Qinghua Zheng, Guang Dai +2
Collecting well-matched multimedia datasets is crucial for training cross-modal retrieval models. However, in real-world scenarios, massive multimodal data are harvested from the I…
Disentangled Representation Learning with Transmitted Information Bottleneck
Zhuohang Dang, Minnan Luo, Chengyou Jia +4
Encoding only the task-related information from the raw data, \ie, disentangled representation learning, can greatly contribute to the robustness and generalizability of models. Al…
PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement
Chengyou Jia, Minnan Luo, Zhuohang Dang +3
Dominant Person Search methods aim to localize and recognize query persons in a unified network, which jointly optimizes two sub-tasks, \ie, pedestrian detection and Re-IDentificat…
Clustering based Point Cloud Representation Learning for 3D Analysis
Tuo Feng, Wenguan Wang, Xiaohan Wang +2
Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the…
Noisy Correspondence Learning with Meta Similarity Correction
Haochen Han, Kaiyao Miao, Qinghua Zheng +1
Despite the success of multimodal learning in cross-modal retrieval task, the remarkable progress relies on the correct correspondence among multimedia data. However, collecting su…
Disentangled Generation with Information Bottleneck for Few-Shot Learning
Zhuohang Dang, Jihong Wang, Minnan Luo +3
Few-shot learning (FSL), which aims to classify unseen classes with few samples, is challenging due to data scarcity. Although various generative methods have been explored for FSL…
Noise-Tolerant Learning for Audio-Visual Action Recognition
Haochen Han, Qinghua Zheng, Minnan Luo +3
Recently, video recognition is emerging with the help of multi-modal learning, which focuses on integrating distinct modalities to improve the performance or robustness of the mode…
CGUA: Context-Guided and Unpaired-Assisted Weakly Supervised Person Search
Chengyou Jia, Minnan Luo, Caixia Yan +2
Recently, weakly supervised person search is proposed to discard human-annotated identities and train the model with only bounding box annotations. A natural way to solve this prob…
Semantics-Guided Contrastive Network for Zero-Shot Object detection
Caixia Yan, Xiaojun Chang, Minnan Luo +3
Zero-shot object detection (ZSD), the task that extends conventional detection models to detecting objects from unseen categories, has emerged as a new challenge in computer vision…