107 citations · 130 across the 9 of their papers we have counts for
9 papers
PartSeg: Few-shot Part Segmentation via Part-aware Prompt Learning
Mengya Han, Heliang Zheng, Chaoyue Wang +4
In this work, we address the task of few-shot part segmentation, which aims to segment the different parts of an unseen object using very few labeled examples. It is found that lev…
Rethinking the Localization in Weakly Supervised Object Localization
Rui Xu, Yong Luo, Han Hu +3
Weakly supervised object localization (WSOL) is one of the most popular and challenging tasks in computer vision. This task is to localize the objects in the images given only the…
Multi-Granularity Hand Action Detection
Ting Zhe, Jing Zhang, Yongqian Li +3
Detecting hand actions in videos is crucial for understanding video content and has diverse real-world applications. Existing approaches often focus on whole-body actions or coarse…
FedABC: Targeting Fair Competition in Personalized Federated Learning
Dui Wang, Li Shen, Yong Luo +4
Federated learning aims to collaboratively train models without accessing their client's local private data. The data may be Non-IID for different clients and thus resulting in poo…
Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE
Qihuang Zhong, Liang Ding, Yibing Zhan +11
This technical report briefly describes our JDExplore d-team's Vega v2 submission on the SuperGLUE leaderboard. SuperGLUE is more challenging than the widely used general language…
Not All Instances Contribute Equally: Instance-adaptive Class Representation Learning for Few-Shot Visual Recognition
Mengya Han, Yibing Zhan, Yong Luo +4
Few-shot visual recognition refers to recognize novel visual concepts from a few labeled instances. Many few-shot visual recognition methods adopt the metric-based meta-learning pa…