activity
20212026
most citedInstant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

26 citations · 45 across the 31 of their papers we have counts for

collaborators

36 papers

cs.CV2026

From Given to Gathered Evidence: Agentic Learning for Longitudinal Medical Reasoning

Minye Shao, Chaohui Yu, Yixuan Wu +6

Foundation models can serve as clinical agents through tool-use harnesses. However, conventional medical benchmarks assess reasoning over preselected evidence rather than the abili…

cs.CV2026

TGRHuman: Text-Guided Realistic 3D Human Generation via Diffusion Renderer

Muxin Zhang, Chaohui Yu, Yuanwang Yang +3

Realistic 3D human generation plays a crucial role in many graphics applications. However, current methods still struggle to generate high-quality human geometry and texture while…

cs.CV2026

SCOPE: Scale-Consistent One-Pass Estimation of 3D Geometry

Zheng Zhang, Lihe Yang, Tianyu Yang +6

We present SCOPE (Scale-Consistent One-Pass Estimation of 3D Geometry), a novel approach for estimating 3D geometry from extended monocular video sequences, where existing methods…

cs.CV2026

Astra: a generalizable report generation foundation model for 3D computed tomography

Zhuhao Wang, Fang Chen, Chaohui Yu +19

Interpreting computed tomography (CT) requires review of hundreds of volumetric slices and remains time-intensive and expertise-dependent. Automated CT report generation offers a p…

cs.CV2026

AnimateAnyMesh++: A Flexible Feed-Forward Framework for High-Fidelity Text-Driven Mesh Animation

Zijie Wu, Chaohui Yu, Fan Wang +1

Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to the complexity of modeling spa…

cs.CV2026

Vascular anatomy-aware self-supervised pre-training for X-ray angiogram analysis

De-Xing Huang, Chaohui Yu, Xiao-Hu Zhou +8

Objective: X-ray angiography is the gold standard imaging modality for cardiovascular diseases. However, current deep learning approaches for X-ray angiogram analysis are severely…

cs.CV2026

A Contrastive Pre-trained Foundation Model for Deciphering Imaging Noisomics across Modalities

Yuanjie Gu, Yiqun Wang, Chaohui Yu +4

Characterizing imaging noise is notoriously data-intensive and device-dependent, as modern sensors entangle physical signals with complex algorithmic artifacts. Current paradigms s…

cs.CV2025

MVRoom: Controllable 3D Indoor Scene Generation with Multi-View Diffusion Models

Shaoheng Fang, Chaohui Yu, Fan Wang +1

We introduce MVRoom, a controllable novel view synthesis (NVS) pipeline for 3D indoor scenes that uses multi-view diffusion conditioned on a coarse 3D layout. MVRoom employs a two-…

cs.CV2025

GeoVideo: Introducing Geometric Regularization into Video Generation Model

Yunpeng Bai, Shaoheng Fang, Chaohui Yu +2

Recent advances in video generation have enabled the synthesis of high-quality and visually realistic clips using diffusion transformer models. However, most existing approaches op…

cs.RO2025

RynnVLA-002: A Unified Vision-Language-Action and World Model

Jun Cen, Siteng Huang, Yuqian Yuan +11

We introduce RynnVLA-002, a unified Vision-Language-Action (VLA) and world model. The world model leverages action and visual inputs to predict future image states, learning the un…

cs.CV2025

CamPVG: Camera-Controlled Panoramic Video Generation with Epipolar-Aware Diffusion

Chenhao Ji, Chaohui Yu, Junyao Gao +2

Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing methods predominantly focus on camer…

cs.CV2025

EarthCrafter: Scalable 3D Earth Generation via Dual-Sparse Latent Diffusion

Shang Liu, Chenjie Cao, Chaohui Yu +3

Despite the remarkable developments achieved by recent 3D generation works, scaling these methods to geographic extents, such as modeling thousands of square kilometers of Earth's…

cs.CV2025

LiON-LoRA: Rethinking LoRA Fusion to Unify Controllable Spatial and Temporal Generation for Video Diffusion

Yisu Zhang, Chenjie Cao, Chaohui Yu +1

Video Diffusion Models (VDMs) have demonstrated remarkable capabilities in synthesizing realistic videos by learning from large-scale data. Although vanilla Low-Rank Adaptation (Lo…

cs.RO2025

WorldVLA: Towards Autoregressive Action World Model

Jun Cen, Chaohui Yu, Hangjie Yuan +9

We present WorldVLA, an autoregressive action world model that unifies action and image understanding and generation. Our WorldVLA intergrates Vision-Language-Action (VLA) model an…

cs.CV2025

AnimateAnyMesh: A Feed-Forward 4D Foundation Model for Text-Driven Universal Mesh Animation

Zijie Wu, Chaohui Yu, Fan Wang +1

Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to the complexity of modeling spa…

cs.CV2025

3DV-TON: Textured 3D-Guided Consistent Video Try-on via Diffusion Models

Min Wei, Chaohui Yu, Jingkai Zhou +1

Video try-on replaces clothing in videos with target garments. Existing methods struggle to generate high-quality and temporally consistent results when handling complex clothing p…

cs.CV2025

Cyc3D: Fine-grained Controllable 3D Generation via Cycle Consistency Regularization

Hongbin Xu, Chaohui Yu, Feng Xiao +5

Despite the remarkable progress of 3D generation, achieving controllability, i.e., ensuring consistency between generated 3D content and input conditions like edge and depth, remai…

cs.CV2025

Uni3C: Unifying Precisely 3D-Enhanced Camera and Human Motion Controls for Video Generation

Chenjie Cao, Jingkai Zhou, Shikai Li +5

Camera and human motion controls have been extensively studied for video generation, but existing approaches typically address them separately, suffering from limited data with hig…

cs.CV2024

MVGenMaster: Scaling Multi-View Generation from Any Image via 3D Priors Enhanced Diffusion Model

Chenjie Cao, Chaohui Yu, Shang Liu +3

We introduce MVGenMaster, a multi-view diffusion model enhanced with 3D priors to address versatile Novel View Synthesis (NVS) tasks. MVGenMaster leverages 3D priors that are warpe…

cs.CV2024

VCD-Texture: Variance Alignment based 3D-2D Co-Denoising for Text-Guided Texturing

Shang Liu, Chaohui Yu, Chenjie Cao +2

Recent research on texture synthesis for 3D shapes benefits a lot from dramatically developed 2D text-to-image diffusion models, including inpainting-based and optimization-based a…

cs.CV2024

MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing

Chenjie Cao, Chaohui Yu, Fan Wang +2

Novel View Synthesis (NVS) and 3D generation have recently achieved prominent improvements. However, these works mainly focus on confined categories or synthetic 3D assets, which a…

cs.CV2024

MeshSegmenter: Zero-Shot Mesh Semantic Segmentation via Texture Synthesis

Ziming Zhong, Yanxu Xu, Jing Li +4

We present MeshSegmenter, a simple yet effective framework designed for zero-shot 3D semantic segmentation. This model successfully extends the powerful capabilities of 2D segmenta…

cs.CV2024

Animate3D: Animating Any 3D Model with Multi-view Video Diffusion

Yanqin Jiang, Chaohui Yu, Chenjie Cao +3

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take a…

cs.CV2024

SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer

Zijie Wu, Chaohui Yu, Yanqin Jiang +3

Recent advances in 2D/3D generative models enable the generation of dynamic 3D objects from a single-view video. Existing approaches utilize score distillation sampling to form the…