activity
20242026
most citedExploring Real&Synthetic Dataset and Linear Attention in Image Restoration

1 citations · 3 across the 21 of their papers we have counts for

collaborators

23 papers

cs.RO2026

Atomic-WAM: Execution-Grounded Atomic-Motion Reasoning for World Action Models

Shijun Shi, Zhe Liu, Zhi Hou +5

World Action Models (WAMs) typically adapt video foundation models to robotic control through joint video and action prediction. However, task-level instructions may leave the next…

cs.CV2026

VicEdit: Learning to Edit Videos from Visual In-Context Examples

Yuji Wang, Teng Hu, Yuheng Chen +6

Despite progress in instruction-based video editing, unimodal textual instructions inherently struggle to convey fine-grained textures and complex dynamics. To bridge this perceptu…

cs.CV2026

PersonaShot: Benchmarking Person-Centric Narrative Continuity in Multi-Shot Video Generation

Yuji Wang, Yuheng Chen, Teng Hu +7

Video generation is rapidly evolving from single-shot clips to multi-shot narratives, where the human character serves as the core narrative anchor. However, existing benchmarks ma…

cs.CV2026

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

Xiao Luo, Mingyang Du, Xin Zhou +5

High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typically requires learning geometr…

cs.CV2026

Cycle-World: Mitigating Error Accumulation in Long-term Video World Models via Reverse-Prediction Cycle Consistency

Zihan Su, Teng Hu, Jiangning Zhang +4

Autoregressive diffusion models have enabled high-quality video generation, yet their sequential nature inherently suffers from error accumulation. In long-horizon video synthesis,…

cs.CV2026

JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation

Yinan Chen, Chuming Lin, Zhennan Chen +12

While instruction-based video editing has seen significant progress, joint audio-visual editing remains constrained by the absence of dedicated datasets and benchmarks. To bridge t…

cs.CV2026

MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data

Teng Hu, Mingchun Lu, Yating Wang +6

Video world models are a foundational generative technology for embodied AI and the Metaverse, yet existing approaches are inherently limited to a single agent observing from a sin…

cs.CV2026

Spatial-Temporal Decoupled Reference Conditioning for Identity-Preserving Text-to-Video Generation

Yuheng Chen, Teng Hu, Yuji Wang +3

Identity-preserving video generation (IPVG) aims to synthesize high-fidelity videos that follow text prompts while faithfully preserving a reference identity. Despite recent progre…

cs.CV2026

L2P: Unlocking Latent Potential for Pixel Generation

Zhennan Chen, Junwei Zhu, Xu Chen +7

Pixel diffusion models have recently regained attention for visual generation. However, training advanced pixel-space models from scratch demands prohibitive computational and data…

cs.LG2026

Towards Customized Multimodal Role-Play

Chao Tang, Jianzong Wu, Qingyu Shi +5

Unified multimodal understanding and generation models enable richer human-AI interaction. Yet jointly customizing a character's persona, dialogue style, and visual identity while…

cs.CV2026

Evolution of Video Generative Foundations

Teng Hu, Jiangning Zhang, Hongrui Huang +7

The rapid advancement of Artificial Intelligence Generated Content (AIGC) has revolutionized video generation, enabling systems ranging from proprietary pioneers like OpenAI's Sora…

cs.CV2025

InstanceV: Instance-Level Video Generation

Yuheng Chen, Teng Hu, Jiangning Zhang +3

Recent advances in text-to-video diffusion models have enabled the generation of high-quality videos conditioned on textual descriptions. However, most existing text-to-video model…

cs.CV2025

One-to-All Animation: Alignment-Free Character Animation and Image Pose Transfer

Shijun Shi, Jing Xu, Zhihang Li +5

Recent advances in diffusion models have greatly improved pose-driven character animation. However, existing methods are limited to spatially aligned reference-pose pairs with matc…

cs.CV2025

UltraGen: High-Resolution Video Generation with Hierarchical Attention

Teng Hu, Jiangning Zhang, Zihan Su +1

Recent advances in video generation have made it possible to produce visually compelling videos, with wide-ranging applications in content creation, entertainment, and virtual real…

cs.CV2025

PolyVivid: Vivid Multi-Subject Video Generation with Cross-Modal Interaction and Enhancement

Teng Hu, Zhentao Yu, Zhengguang Zhou +4

Despite recent advances in video generation, existing models still lack fine-grained controllability, especially for multi-subject customization with consistent identity and intera…

cs.CV2025★ 1 cited

Image Inversion: A Survey from GANs to Diffusion and Beyond

Yinan Chen, Jiangning Zhang, Yali Bi +6

Image inversion is a fundamental task in generative models, aiming to map images back to their latent representations to enable downstream applications such as editing, restoration…

cs.AI2025

ImitDiff: Transferring Foundation-Model Priors for Distraction Robust Visuomotor Policy

Yuhang Dong, Haizhou Ge, Yupei Zeng +9

Visuomotor imitation learning policies enable robots to efficiently acquire manipulation skills from visual demonstrations. However, as scene complexity and visual distractions inc…

cs.CV2025

Improving Autoregressive Visual Generation with Cluster-Oriented Token Prediction

Teng Hu, Jiangning Zhang, Ran Yi +5

Employing LLMs for visual generation has recently become a research focus. However, the existing methods primarily transfer the LLM architecture to visual generation but rarely inv…

cs.CV2024★ 1 cited

Exploring Real&Synthetic Dataset and Linear Attention in Image Restoration

Yuzhen Du, Teng Hu, Jiangning Zhang +6

Image restoration (IR) aims to recover high-quality images from degraded inputs, with recent deep learning advancements significantly enhancing performance. However, existing metho…

cs.CV2024★ 1 cited

Textual Decomposition Then Sub-motion-space Scattering for Open-Vocabulary Motion Generation

Ke Fan, Jiangning Zhang, Ran Yi +6

Text-to-motion generation is a crucial task in computer vision, which generates the target 3D motion by the given text. The existing annotated datasets are limited in scale, result…

cs.CV2024

SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation

Teng Hu, Jiangning Zhang, Ran Yi +3

In recent years, the development of diffusion models has led to significant progress in image and video generation tasks, with pre-trained models like the Stable Diffusion series p…

cs.CV2024

SuperSVG: Superpixel-based Scalable Vector Graphics Synthesis

Teng Hu, Ran Yi, Baihong Qian +3

SVG (Scalable Vector Graphics) is a widely used graphics format that possesses excellent scalability and editability. Image vectorization, which aims to convert raster images to SV…

cs.CV2024

ID-Sculpt: ID-aware 3D Head Generation from Single In-the-wild Portrait Image

Jinkun Hao, Junshu Tang, Jiangning Zhang +7

While recent works have achieved great success on image-to-3D object generation, high quality and fidelity 3D head generation from a single image remains a great challenge. Previou…