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Bin Tang

7 accepted papers

2026

From Semantics to Spectrum: A New Lens on Graph Augmentation Strategy

AAAI 2026technical

Graph augmentation is a cornerstone of effective graph contrastive learning, yet existing methods often rely on random designed perturbations, which may distort latent semantics and impair representation quality. In this work, we argue that semantic consistency can be effectively approximated by low

Cited by 0SourcePDFScholar
2025

Pose as a Modality: A Psychology-Inspired Network for Personality Recognition with a New Multimodal Dataset

AAAI 2025technical

In recent years, predicting Big Five personality traits from multimodal data has received significant attention in artificial intelligence (AI). However, existing computational models often fail to achieve satisfactory performance. Psychological research has shown a strong correlation between pose a…

Cited by 0SourcePDFScholar
2024

Learned Video Compression with Spatial-Temporal Optimization

ICASSP 2024accepted

Previous optical flow based video compression is gradually replaced by unsupervised deformable convolution (DCN) based method. This is mainly due to the fact that the motion vector (MV) estimated by the existing optical flow network is not accurate and may introduce extra artifacts. However, DCN bas…

Cited by 0SourceScholar