activity
20202024
most citedAchieving adjustable elasticity with non-affine to affine transition

36 citations · 136 across the 25 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cs.CV2024

MotionGPT-2: A General-Purpose Motion-Language Model for Motion Generation and Understanding

Yuan Wang, Di Huang, Yaqi Zhang +5

Generating lifelike human motions from descriptive texts has experienced remarkable research focus in the recent years, propelled by the emerging requirements of digital humans.Des…

cs.AI2024★ 4 cited

Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System

Haoyang Su, Renqi Chen, Shixiang Tang +10

The rapid advancement of scientific progress requires innovative tools that can accelerate knowledge discovery. Although recent AI methods, particularly large language models (LLMs…

cs.CV2024

Holistic-Motion2D: Scalable Whole-body Human Motion Generation in 2D Space

Yuan Wang, Zhao Wang, Junhao Gong +8

In this paper, we introduce a novel path to human motion generation by focusing on 2D space. Traditional methods have primarily generated human motions in 3D, wh…

cs.CE2024★ 2 cited

AFBench: A Large-scale Benchmark for Airfoil Design

Jian Liu, Jianyu Wu, Hairun Xie +8

Data-driven generative models have emerged as promising approaches towards achieving efficient mechanical inverse design. However, due to prohibitively high cost in time and money,…

cs.CV2024★ 4 cited

A Comprehensive Survey on 3D Content Generation

Jian Liu, Xiaoshui Huang, Tianyu Huang +8

Recent years have witnessed remarkable advances in artificial intelligence generated content(AIGC), with diverse input modalities, e.g., text, image, video, audio and 3D. The 3D is…

cs.CV2024

Agent3D-Zero: An Agent for Zero-shot 3D Understanding

Sha Zhang, Di Huang, Jiajun Deng +4

The ability to understand and reason the 3D real world is a crucial milestone towards artificial general intelligence. The current common practice is to finetune Large Language Mod…

cs.CV2024

DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM

Yixuan Wu, Yizhou Wang, Shixiang Tang +5

We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object detection ability of multimodal large language models (MLLMs), such as GPT-4V and Gemini. Our a…