activity
20232026
most citedSEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction

12 citations · 36 across the 32 of their papers we have counts for

collaborators

40 papers

cs.CV2026

Intern Lumina U2: A Multi-Codebook Diffusion Large Language Model for Omni-Visual Understanding and Image Generation

Qian Yu, Zongyang Qiu, Juncheng Yan +40

Unified multimodal generation covers discrete, continuous, and hybrid paradigms. Discrete approaches with single-codebook visual tokenizers align naturally with text modeling but h…

cs.CV2026

CineMem: Attention-Aligned Fine-grained Memory Retrieval for Multi-Shot Long Video Generation

Xiaoxue Wu, Xinyu Gao, Fang Yu +2

Autoregressive video generation relies on memory retrieval to model long-range dependencies. This capability becomes particularly critical for multi-shot generation, where models m…

cs.CV2026

FlashVSR+: Efficient Video Super-Resolution via Hybrid Attention and Reward-Yield Distribution Matching

Ruchang Yao, Shi Guo, Junhao Zhuang +7

Recent video super-resolution (VSR) models achieve efficient one-step generation through diffusion distillation. However, high-resolution inference remains costly, and distilled mo…

cs.CV2026

VDOT++: Unified Few-Step Video Generation via Unbalanced Optimal Transport Distillation

Yutong Wang, Xingtong Ge, Enhuai Liu +6

Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they repeatedly evaluate large back…

cs.CV2026

PulseQuant: Propagation-Guided Subspace Correction for 4-Bit Video Diffusion Transformers

Yutong Wang, Xingtong Ge, Enhuai Liu +4

Quantization errors in video diffusion transformers can be amplified or attenuated by subsequent denoising updates, making local reconstruction error an incomplete predictor of fin…

cs.CV2026

Diff-VF: Training-free High-quality Long Video Generation via Diffusion Model

Haoning Yang, Xinyuan Chen, Yaohui Wang +1

Recently, diffusion models have made great progress in video generation. However, most existing video diffusion models are trained with short videos, and degrade when extrapolated…

cs.CV2026

DeforM: Reasoning-Guided Physics-Aware Video Generation via Spatial-Temporal Masking

Yunyi Li, Yu Qiao, Yaohui Wang +1

Video generation models achieve high visual quality but often struggle to generate physics-aware videos. Unlike rigid-body motion, which can be described by explicit trajectories o…

cs.AI2026

A Definition and Roadmap for World Models

Xinyuan Chen, Haoyu Guo, Shi Guo +10

World models -- internal simulators that learn the structure and dynamics of an environment -- have become one of the most actively debated concepts in AI. From model-based reinfor…

cs.CV2026

Inclusive Interactive Collisions for Multi-View Consistent Compositional 3D Generation

Chang Liu, Mingwen Shao, Xiang Lv +5

Recent breakthroughs in 3D generation have advanced notably with the development of text-to-image diffusion model. However, existing methods remain two practical challenges: (1) Th…

cs.CV2026

Policy-as-Data: Learning Generalizable HOI Diffusion Models from Simulated Physics

Shujia Li, Jianshu Hu, Haiyu Zhang +5

Synthesizing realistic Human-Object Interactions (HOI) is critical for creating embodied avatars and functional virtual environments. However, current data-driven approaches primar…

cs.CV2026

CausalMotion: Structured Physical Reasoning as Keyframe and Trajectory Guidance for Training-Free Video Generation

Sihan Zhuang, Xinyuan Chen, Tianfan Xue +1

Recent advances in diffusion-based video generation have significantly improved visual quality and short-term temporal coherence. However, existing methods still struggle to produc…

cs.CV2026

PARE: Pruning and Adaptive Routing for Efficient Video Generation

Yutong Wang, Yunke Wang, Tianfan Xue +4

Video Diffusion Transformers (DiTs) generate high-quality videos but demand substantial compute due to wide blocks, deep architectures, and iterative sampling. Recent methods reduc…

cs.CV2026

BEAT: Rhythm-Elastic Alignment for Agentic Music-guided Movie Trailer Generation

Yutong Wang, Yunke Wang, Xinyuan Chen +1

Automatic movie trailer generation must select shots from a full-length film and synchronize them with background music. Existing methods either relegate music alignment to post-pr…

cs.CV2026

Uni-Animator: Towards Unified Visual Colorization

Xinyuan Chen, Yao Xu, Shaowen Wang +2

We propose Uni-Animator, a novel Diffusion Transformer (DiT)-based framework for unified image and video sketch colorization. Existing sketch colorization methods struggle to unify…

cs.CV2025

VDOT: Efficient Unified Video Creation via Optimal Transport Distillation

Yutong Wang, Haiyu Zhang, Tianfan Xue +4

The rapid development of generative models has significantly advanced image and video applications. Among these, video creation, aimed at generating videos under various conditions…

cs.CV2025

ShotDirector: Directorially Controllable Multi-Shot Video Generation with Cinematographic Transitions

Xiaoxue Wu, Xinyuan Chen, Yaohui Wang +1

Shot transitions play a pivotal role in multi-shot video generation, as they determine the overall narrative expression and the directorial design of visual storytelling. However,…

cs.CV2025

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling

Bingjie Gao, Qianli Ma, Xiaoxue Wu +9

Prompt design plays a crucial role in text-to-video (T2V) generation, yet user-provided prompts are often short, unstructured, and misaligned with training data, limiting the gener…

cs.CV2025

LIA-X: Interpretable Latent Portrait Animator

Yaohui Wang, Di Yang, Xinyuan Chen +3

We introduce LIA-X, a novel interpretable portrait animator designed to transfer facial dynamics from a driving video to a source portrait with fine-grained control. LIA-X is an au…

cs.CV2025

Consistent and Controllable Image Animation with Motion Linear Diffusion Transformers

Xin Ma, Yaohui Wang, Genyun Jia +3

Image animation has seen significant progress, driven by the powerful generative capabilities of diffusion models. However, maintaining appearance consistency with static input ima…

cs.CV2025

CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Models

Xiaoxue Wu, Bingjie Gao, Yu Qiao +2

Despite significant advances in video synthesis, research into multi-shot video generation remains in its infancy. Even with scaled-up models and massive datasets, the shot transit…

cs.CV2025

GenHOI: Generalizing Text-driven 4D Human-Object Interaction Synthesis for Unseen Objects

Shujia Li, Haiyu Zhang, Xinyuan Chen +2

While diffusion models and large-scale motion datasets have advanced text-driven human motion synthesis, extending these advances to 4D human-object interaction (HOI) remains chall…

cs.CV2025

Training-free Stylized Text-to-Image Generation with Fast Inference

Xin Ma, Yaohui Wang, Xinyuan Chen +2

Although diffusion models exhibit impressive generative capabilities, existing methods for stylized image generation based on these models often require textual inversion or fine-t…

cs.CV2025

The Devil is in the Prompts: Retrieval-Augmented Prompt Optimization for Text-to-Video Generation

Bingjie Gao, Xinyu Gao, Xiaoxue Wu +5

The evolution of Text-to-video (T2V) generative models, trained on large-scale datasets, has been marked by significant progress. However, the sensitivity of T2V generative models…

cs.CV2025

AccVideo: Accelerating Video Diffusion Model with Synthetic Dataset

Haiyu Zhang, Xinyuan Chen, Yaohui Wang +3

Diffusion models have achieved remarkable progress in the field of video generation. However, their iterative denoising nature requires a large number of inference steps to generat…