95 citations · 210 across the 17 of their papers we have counts for
7 papers · 1 filter
Dual-view Curricular Optimal Transport for Cross-lingual Cross-modal Retrieval
Yabing Wang, Shuhui Wang, Hao Luo +5
Current research on cross-modal retrieval is mostly English-oriented, as the availability of a large number of English-oriented human-labeled vision-language corpora. In order to b…
Region Generation and Assessment Network for Occluded Person Re-Identification
Shuting He, Weihua Chen, Kai Wang +4
Person Re-identification (ReID) plays a more and more crucial role in recent years with a wide range of applications. Existing ReID methods are suffering from the challenges of mis…
SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels
Henry Hengyuan Zhao, Pichao Wang, Yuyang Zhao +3
Pre-trained vision transformers have strong representation benefits to various downstream tasks. Recently, many parameter-efficient fine-tuning (PEFT) methods have been proposed, a…
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang +4
Unsupervised Contrastive learning has gained prominence in fields such as vision, and biology, leveraging predefined positive/negative samples for representation learning. Data aug…
Efficient Token-Guided Image-Text Retrieval with Consistent Multimodal Contrastive Training
Chong Liu, Yuqi Zhang, Hongsong Wang +5
Image-text retrieval is a central problem for understanding the semantic relationship between vision and language, and serves as the basis for various visual and language tasks. Mo…
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
Weihua Chen, Xianzhe Xu, Jian Jia +5
Human-centric visual tasks have attracted increasing research attention due to their widespread applications. In this paper, we aim to learn a general human representation from mas…
Revisit Parameter-Efficient Transfer Learning: A Two-Stage Paradigm
Hengyuan Zhao, Hao Luo, Yuyang Zhao +3
Parameter-Efficient Transfer Learning (PETL) aims at efficiently adapting large models pre-trained on massive data to downstream tasks with limited task-specific data. In view of t…