activity
20232026
most citedMultimodal Action Quality Assessment

49 citations · 72 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2026

PhysiGen: Integrating Collision-Aware Physical Constraints for High-Fidelity Human-Human Interaction Generation

Nan Lei, Yuan-Ming Li, Ling-An Zeng +5

Despite substantial progress in text-driven 3D human motion synthesis, generating realistic multi-person interaction sequences remains challenging. Notably, body inter-penetration…

cs.CV2025★ 4 cited

Progressive Human Motion Generation Based on Text and Few Motion Frames

Ling-An Zeng, Gaojie Wu, Ancong Wu +2

Although existing text-to-motion (T2M) methods can produce realistic human motion from text description, it is still difficult to align the generated motion with the desired postur…

cs.CV2025

Efficient Explicit Joint-level Interaction Modeling with Mamba for Text-guided HOI Generation

Guohong Huang, Ling-An Zeng, Zexin Zheng +2

We propose a novel approach for generating text-guided human-object interactions (HOIs) that achieves explicit joint-level interaction modeling in a computationally efficient manne…

cs.CV2025

ChainHOI: Joint-based Kinematic Chain Modeling for Human-Object Interaction Generation

Ling-An Zeng, Guohong Huang, Yi-Lin Wei +4

We propose ChainHOI, a novel approach for text-driven human-object interaction (HOI) generation that explicitly models interactions at both the joint and kinetic chain levels. Unli…

cs.CV2024

Light-T2M: A Lightweight and Fast Model for Text-to-motion Generation

Ling-An Zeng, Guohong Huang, Gaojie Wu +1

Despite the significant role text-to-motion (T2M) generation plays across various applications, current methods involve a large number of parameters and suffer from slow inference…

cs.CV2024

PRET: Planning with Directed Fidelity Trajectory for Vision and Language Navigation

Renjie Lu, Jingke Meng, Wei-Shi Zheng

Vision and language navigation is a task that requires an agent to navigate according to a natural language instruction. Recent methods predict sub-goals on constructed topology ma…

cs.CV2024

EgoExo-Fitness: Towards Egocentric and Exocentric Full-Body Action Understanding

Yuan-Ming Li, Wei-Jin Huang, An-Lan Wang +3

We present EgoExo-Fitness, a new full-body action understanding dataset, featuring fitness sequence videos recorded from synchronized egocentric and fixed exocentric (third-person)…

cs.CV2024

Rethinking Few-shot Class-incremental Learning: Learning from Yourself

Yu-Ming Tang, Yi-Xing Peng, Jingke Meng +1

Few-shot class-incremental learning (FSCIL) aims to learn sequential classes with limited samples in a few-shot fashion. Inherited from the classical class-incremental learning set…

eess.SP2024★ 49 cited

Multimodal Action Quality Assessment

Ling-An Zeng, Wei-Shi Zheng

Action quality assessment (AQA) is to assess how well an action is performed. Previous works perform modelling by only the use of visual information, ignoring audio information. We…

cs.CV2023

Cross-Modal Adaptive Dual Association for Text-to-Image Person Retrieval

Dixuan Lin, Yixing Peng, Jingke Meng +1

Text-to-image person re-identification (ReID) aims to retrieve images of a person based on a given textual description. The key challenge is to learn the relations between detailed…

cs.CV2023★ 19 cited

Continual Action Assessment via Task-Consistent Score-Discriminative Feature Distribution Modeling

Yuan-Ming Li, Ling-An Zeng, Jing-Ke Meng +1

Action Quality Assessment (AQA) is a task that tries to answer how well an action is carried out. While remarkable progress has been achieved, existing works on AQA assume that all…