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Ling-An Zeng

8 accepted papers

2026

MotionHiFlow: Text-to-Motion via Hierarchical Flow Matching

CVPR 2026

Text-to-motion generation aims to generate 3D human motions that are tightly aligned with the input text while remaining physically plausible and rich in fine-grained detail. Although recent approaches can produce complex and natural movements, they usually operate at only one temporal scale, which

Cited by 2SourcecodeScholar
2025

AffordDexGrasp: Open-set Language-guided Dexterous Grasp with Generalizable-Instructive Affordance

ICCV 2025poster

Language-guided robot dexterous generation enables robots to grasp and manipulate objects based on human commands. However, previous data-driven methods are hard to understand intention and execute grasping with unseen categories in the open set. In this work, we explore a new task, Open-set Languag…

Cited by 0SourcePDFScholar
2025

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

CVPR 2025poster

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. Unlike existing methods that implicitly model interactions using full-body poses as tokens, we argue that explicitly mode…

Cited by 2SourcePDFScholar
2025

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

AAAI 2025technical

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 speeds, leading to high usage costs. To address this, we aim to design a lightweight model to reduce usage costs. First,…

2025

Rethinking Bimanual Robotic Manipulation: Learning with Decoupled Interaction Framework

ICCV 2025poster

Bimanual robotic manipulation is an emerging and critical topic in the robotics community. Previous works primarily rely on integrated control models that take the perceptions and states of both arms as inputs to directly predict their actions. However, we think bimanual manipulation involves not on…

Cited by 0SourcePDFScholar
2024

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

ECCV 2024poster

"We present EgoExo-Fitness, a new full-body action understanding dataset, featuring fitness sequence videos recorded from synchronized egocentric and fixed exocentric (third-person) cameras. Compared with existing full-body action understanding datasets, EgoExo-Fitness not only contains videos from…