111 citations · 126 across the 6 of their papers we have counts for
6 papers
Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks
Hao Li, Jinguo Zhu, Xiaohu Jiang +8
Despite the remarkable success of foundation models, their task-specific fine-tuning paradigm makes them inconsistent with the goal of general perception modeling. The key to elimi…
Semantic Data Augmentation based Distance Metric Learning for Domain Generalization
Mengzhu Wang, Jianlong Yuan, Qi Qian +2
Domain generalization (DG) aims to learn a model on one or more different but related source domains that could be generalized into an unseen target domain. Existing DG methods try…
MimCo: Masked Image Modeling Pre-training with Contrastive Teacher
Qiang Zhou, Chaohui Yu, Hao Luo +2
Recent masked image modeling (MIM) has received much attention in self-supervised learning (SSL), which requires the target model to recover the masked part of the input image. Alt…
On Representation Learning with Feedback
Hao Li
This note complements the author's recent paper "Robust representation learning with feedback for single image deraining" by providing heuristically theoretical explanations on the…
Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks
Xizhou Zhu, Jinguo Zhu, Hao Li +5
Biological intelligence systems of animals perceive the world by integrating information in different modalities and processing simultaneously for various tasks. In contrast, curre…
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
Tongkun Xu, Weihua Chen, Pichao Wang +3
Unsupervised domain adaptation (UDA) aims to transfer knowledge learned from a labeled source domain to a different unlabeled target domain. Most existing UDA methods focus on lear…