activity
20232026
most citedMeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

8 citations · 20 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens

Yiying Yang, Wei Cheng, Sijin Chen +5

OmniLottie is a versatile framework that generates high quality vector animations from multi-modal instructions. For flexible motion and visual content control, we focus on Lottie,…

cs.CV2025

OmniSVG: A Unified Scalable Vector Graphics Generation Model

Yiying Yang, Wei Cheng, Sijin Chen +7

Scalable Vector Graphics (SVG) is an important image format widely adopted in graphic design because of their resolution independence and editability. The study of generating high-…

cs.CV2024★ 6 cited

MeshXL: Neural Coordinate Field for Generative 3D Foundation Models

Sijin Chen, Xin Chen, Anqi Pang +11

The polygon mesh representation of 3D data exhibits great flexibility, fast rendering speed, and storage efficiency, which is widely preferred in various applications. However, giv…

cs.CV2024★ 8 cited

MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Yiwen Chen, Tong He, Di Huang +9

Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement. However, this poten…

cs.CV2023★ 5 cited

M3DBench: Let's Instruct Large Models with Multi-modal 3D Prompts

Mingsheng Li, Xin Chen, Chi Zhang +5

Recently, 3D understanding has become popular to facilitate autonomous agents to perform further decisionmaking. However, existing 3D datasets and methods are often limited to spec…

cs.CV2023★ 1 cited

LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning

Sijin Chen, Xin Chen, Chi Zhang +6

Recent advances in Large Multimodal Models (LMM) have made it possible for various applications in human-machine interactions. However, developing LMMs that can comprehend, reason,…

cs.CV2023

Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning

Sijin Chen, Hongyuan Zhu, Mingsheng Li +6

3D dense captioning requires a model to translate its understanding of an input 3D scene into several captions associated with different object regions. Existing methods adopt a so…