Search Results for author: Bochao Zou

Found 5 papers, 3 papers with code

Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training

no code implementations25 Sep 2024 Kun Song, Zhiquan Tan, Bochao Zou, Jiansheng Chen, Huimin Ma, Weiran Huang

Experiments show that matrix entropy cannot solely describe the interaction of the information content of data representation and classification head weights but it can effectively reflect the similarity and clustering behavior of the data.

Classification cross-modal alignment

Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transition

1 code implementation15 Sep 2024 Bochao Zou, Zizheng Guo, Wenfeng Qin, Xin Li, Kangsheng Wang, Huimin Ma

The analysis of micro-expressions generally involves two main tasks: spotting micro-expression intervals in long videos and recognizing the emotions associated with these intervals.

Classification

Unveiling the Dynamics of Information Interplay in Supervised Learning

no code implementations6 Jun 2024 Kun Song, Zhiquan Tan, Bochao Zou, Huimin Ma, Weiran Huang

In this paper, we use matrix information theory as an analytical tool to analyze the dynamics of the information interplay between data representations and classification head vectors in the supervised learning process.

Linear Mode Connectivity

RhythmMamba: Fast Remote Physiological Measurement with Arbitrary Length Videos

1 code implementation9 Apr 2024 Bochao Zou, Zizheng Guo, Xiaocheng Hu, Huimin Ma

Remote photoplethysmography (rPPG) is a non-contact method for detecting physiological signals from facial videos, holding great potential in various applications such as healthcare, affective computing, and anti-spoofing.

Mamba

RhythmFormer: Extracting rPPG Signals Based on Hierarchical Temporal Periodic Transformer

1 code implementation20 Feb 2024 Bochao Zou, Zizheng Guo, Jiansheng Chen, Huimin Ma

Due to the periodicity nature of rPPG, the long-range dependency capturing capacity of the Transformer was assumed to be advantageous for such signals.

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