3 citations · 4 across the 6 of their papers we have counts for
6 papers
Low-Rank Mixture-of-Experts for Continual Medical Image Segmentation
Qian Chen, Lei Zhu, Hangzhou He +4
The primary goal of continual learning (CL) task in medical image segmentation field is to solve the "catastrophic forgetting" problem, where the model totally forgets previously l…
Beyond Text: Frozen Large Language Models in Visual Signal Comprehension
Lei Zhu, Fangyun Wei, Yanye Lu
In this work, we investigate the potential of a large language model (LLM) to directly comprehend visual signals without the necessity of fine-tuning on multi-modal datasets. The f…
Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation
Lei Zhu, Hangzhou He, Xinliang Zhang +4
End-to-end weakly supervised semantic segmentation aims at optimizing a segmentation model in a single-stage training process based on only image annotations. Existing methods adop…
One-Pot Multi-Frame Denoising
Lujia Jin, Shi Zhao, Lei Zhu +2
The performance of learning-based denoising largely depends on clean supervision. However, it is difficult to obtain clean images in many scenes. On the contrary, the capture of mu…
Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization
Lei Zhu, Qian Chen, Lujia Jin +2
Classification activation map (CAM), utilizing the classification structure to generate pixel-wise localization maps, is a crucial mechanism for weakly supervised object localizati…
Background-aware Classification Activation Map for Weakly Supervised Object Localization
Lei Zhu, Qi She, Qian Chen +9
Weakly supervised object localization (WSOL) relaxes the requirement of dense annotations for object localization by using image-level classification masks to supervise its learnin…