activity
20232026
most citedInteractive3D: Create What You Want by Interactive 3D Generation

1 citations · 1 across the 11 of their papers we have counts for

collaborators

14 papers

cs.LG2026

Hilbert-Scale Stability of Posterior Diffusion Priors for Ill-Posed Signal Recovery

Bahman Moraffah, Raha Moraffah

Indirect and noisy observations are difficult to invert when the forward operator smooths out the unknown signal. In this case, the unstable modes are precisely the modes that the…

cs.RO2026

Systematically Exploring the Capabilities of GPT-6 Astra as Embodied Policies

Galbot Team, Xuchuan Chen, Xiaoqian Cheng +31

GPT-6 Astra exhibits a remarkable ability to generate numerical robot actions, extending its role beyond high-level planning. To assess Astra's capabilities as general-purpose embo…

cs.RO2026

RoboSynChallenge: Mastering Real-World Dexterity via Generalizing Synthesized Manipulation Skills

Runyi Zhao, Ruixin Wu, Chengkun Li +15

Achieving generalizable robotic manipulation remains a central challenge in embodied intelligence. Despite rapid advances in model architectures and learning algorithms, progress i…

cs.RO2026

ReactiveBFM: Reactive Closed-Loop Motion Planning Towards Universal Humanoid Whole-Body Control

Xiao Chen, Weishuai Zeng, Xiaojie Niu +12

While current Behavior Foundation Models (BFMs) provide robust control priors for humanoids, they only execute pre-defined reference motions. As a result, they are vulnerable to en…

cs.CV2025

DynamicTree: Interactive Real Tree Animation via Sparse Voxel Spectrum

Yaokun Li, Lihe Ding, Xiao Chen +2

Generating dynamic and interactive 3D trees has wide applications in virtual reality, games, and world simulation. However, existing methods still face various challenges in genera…

cs.CV2025

FullPart: Generating each 3D Part at Full Resolution

Lihe Ding, Shaocong Dong, Yaokun Li +10

Part-based 3D generation holds great potential for various applications. Previous part generators that represent parts using implicit vector-set tokens often suffer from insufficie…

cs.CV2025

DiffIER: Optimizing Diffusion Models with Iterative Error Reduction

Ao Chen, Lihe Ding, Tianfan Xue

Diffusion models have demonstrated remarkable capabilities in generating high-quality samples and enhancing performance across diverse domains through Classifier-Free Guidance (CFG…

cs.CV2025

From Gallery to Wrist: Realistic 3D Bracelet Insertion in Videos

Chenjian Gao, Lihe Ding, Rui Han +3

Inserting 3D objects into videos is a longstanding challenge in computer graphics with applications in augmented reality, virtual try-on, and video composition. Achieving both temp…

cs.CV2025

From One to More: Contextual Part Latents for 3D Generation

Shaocong Dong, Lihe Ding, Xiao Chen +10

Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth da…

cs.CV2025

4DSloMo: 4D Reconstruction for High Speed Scene with Asynchronous Capture

Yutian Chen, Shi Guo, Tianshuo Yang +4

Reconstructing fast-dynamic scenes from multi-view videos is crucial for high-speed motion analysis and realistic 4D reconstruction. However, the majority of 4D capture systems are…

cs.CV2025

LoRA-Edit: Controllable First-Frame-Guided Video Editing via Mask-Aware LoRA Fine-Tuning

Chenjian Gao, Lihe Ding, Xin Cai +3

Video editing using diffusion models has achieved remarkable results in generating high-quality edits for videos. However, current methods often rely on large-scale pretraining, li…

cs.GR2024★ 1 cited

Interactive3D: Create What You Want by Interactive 3D Generation

Shaocong Dong, Lihe Ding, Zhanpeng Huang +3

3D object generation has undergone significant advancements, yielding high-quality results. However, fall short of achieving precise user control, often yielding results that do no…

cs.CV2023

Text-to-3D Generation with Bidirectional Diffusion using both 2D and 3D priors

Lihe Ding, Shaocong Dong, Zhanpeng Huang +5

Most 3D generation research focuses on up-projecting 2D foundation models into the 3D space, either by minimizing 2D Score Distillation Sampling (SDS) loss or fine-tuning on multi-…

cs.CV2023

Obj-NeRF: Extract Object NeRFs from Multi-view Images

Zhiyi Li, Lihe Ding, Tianfan Xue

Neural Radiance Fields (NeRFs) have demonstrated remarkable effectiveness in novel view synthesis within 3D environments. However, extracting a radiance field of one specific objec…