9 papers
Task-disentangled Low-Rank Adaptation for Versatile Audio-visual Multi-modal Learning Tasks within a Unified Framework
Hanyu Xuan, Mengqi Zhang, Junjun Mao +5
Inspired by human multi-modal perception, Audio-Visual Multi-Modal Learning (AVMML) integrates auditory and visual information to leverage complementary cross-modal cues, enabling…
3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models
Xinye Zheng, Fei Wang, Yiqi Nie +5
Reconstructing 3D scenes from smoke-degraded multi-view images is particularly difficult because smoke introduces strong scattering effects, view-dependent appearance changes, and…
MA-Bench: Towards Fine-grained Micro-Action Understanding
Kun Li, Jihao Gu, Fei Wang +3
With the rapid development of Multimodal Large Language Models (MLLMs), their potential in Micro-Action understanding, a vital role in human emotion analysis, remains unexplored du…
Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs
Yixiao Zhou, Ziyu Zhao, Dongzhou Cheng +6
Sparse Mixture-of-Experts (SMoE) architectures are widely used in large language models (LLMs) due to their computational efficiency. However, though only a few experts are activat…
MM-Gesture: Towards Precise Micro-Gesture Recognition through Multimodal Fusion
Jihao Gu, Fei Wang, Kun Li +3
In this paper, we present MM-Gesture, the solution developed by our team HFUT-VUT, which ranked 1st in the micro-gesture classification track of the 3rd MiGA Challenge at IJCAI 202…
Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition
Jihao Gu, Kun Li, Fei Wang +4
Micro-Actions (MAs) are an important form of non-verbal communication in social interactions, with potential applications in human emotional analysis. However, existing methods in…