1 citations · 1 across the 4 of their papers we have counts for
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Reshaping the Online Data Buffering and Organizing Mechanism for Continual Test-Time Adaptation
Zhilin Zhu, Xiaopeng Hong, Zhiheng Ma +4
Continual Test-Time Adaptation (CTTA) involves adapting a pre-trained source model to continually changing unsupervised target domains. In this paper, we systematically analyze the…
Prompt Customization for Continual Learning
Yong Dai, Xiaopeng Hong, Yabin Wang +3
Contemporary continual learning approaches typically select prompts from a pool, which function as supplementary inputs to a pre-trained model. However, this strategy is hindered b…
Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling
Hui Lin, Zhiheng Ma, Rongrong Ji +4
This paper focuses on semi-supervised crowd counting, where only a small portion of the training data are labeled. We formulate the pixel-wise density value to regress as a probabi…
Semi-supervised Crowd Counting via Density Agency
Hui Lin, Zhiheng Ma, Xiaopeng Hong +2
In this paper, we propose a new agency-guided semi-supervised counting approach. First, we build a learnable auxiliary structure, namely the density agency to bring the recognized…