activity
20232025
most citedMesh-Guided Neural Implicit Field Editing

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

I2V3D: Controllable image-to-video generation with 3D guidance

Zhiyuan Zhang, Dongdong Chen, Jing Liao

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced gene…

cs.CV2024

SGEdit: Bridging LLM with Text2Image Generative Model for Scene Graph-based Image Editing

Zhiyuan Zhang, DongDong Chen, Jing Liao

Scene graphs offer a structured, hierarchical representation of images, with nodes and edges symbolizing objects and the relationships among them. It can serve as a natural interfa…

cs.CV2024

Chat2Layout: Interactive 3D Furniture Layout with a Multimodal LLM

Can Wang, Hongliang Zhong, Menglei Chai +3

Automatic furniture layout is long desired for convenient interior design. Leveraging the remarkable visual reasoning capabilities of multimodal large language models (MLLMs), rece…

cs.CV2023★ 1 cited

Mesh-Guided Neural Implicit Field Editing

Can Wang, Mingming He, Menglei Chai +2

Neural implicit fields have emerged as a powerful 3D representation for reconstructing and rendering photo-realistic views, yet they possess limited editability. Conversely, explic…

cs.CV2023★ 1 cited

HairCLIPv2: Unifying Hair Editing via Proxy Feature Blending

Tianyi Wei, Dongdong Chen, Wenbo Zhou +4

Hair editing has made tremendous progress in recent years. Early hair editing methods use well-drawn sketches or masks to specify the editing conditions. Even though they can enabl…