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20232026
most citedDyna-DepthFormer: Multi-frame Transformer for Self-Supervised Depth Estimation in Dynamic Scenes

2 citations · 4 across the 17 of their papers we have counts for

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Showing 2026 · cs.CVShow all

14 papers · 2 filters

cs.CV2026

WorldStream: Streaming Interactive 3D Worlds with Hierarchical Planning and Persistent State

Xiaoxiao Ma, Weiyang Jin, Yanwen Ma +11

We present WorldStream, an open-ended 3D world model with three simultaneous capabilities: it extends playable terrain beyond any pre-specified map, acts on open-ended language in…

cs.CV2026

Mask Forcing: Improving Autoregressive Video Diffusion Distillation via Dual-Noise Masking Rollout

Zhuoran Zhao, Shengju Qian, Tongtong Liang +7

Autoregressive (AR) video diffusion models have shown great potential in real-time video generation. Recent methods distill pretrained bidirectional video diffusion models into cau…

cs.CV2026

Building Pretraining Data for World Models: An Unreal Engine-Based Pipeline for Action-Conditioned Video Generation

Haoyu Wang, Songchun Zhang, Haoran Li +3

Action-conditioned video models require large-scale visual data paired with control signals that are temporally aligned with the resulting scene transitions. Such supervision is di…

cs.CV2026

Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds

Nan Duan, Haoyang Huang, Weiyang Jin +13

Video generation is progressing beyond isolated clips toward long-form narratives and interactive worlds, requiring models to preserve identities, follow user controls, and remain…

cs.CV2026

EchoWM: Open and Enterable Omnimodal World Models

Songchun Zhang, Yaowei Li, Junhao Zhuang +19

We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, environmental sound, music an…

cs.CV2026

LiveLight: Real-time Streaming Video Relighting with Interactive Control

Yue Ma, Jiangming Wang, Yucheng Wang +8

We present LiveLight, the first diffusion-based framework for real-time streaming video relighting with interactive 3D lighting control. Achieving this is non-trivial, as it requir…

cs.CV2026

FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control

Songchun Zhang, Sitong Guo, Xianghao Kong +4

Generative video compositing, which involves inserting external assets seamlessly into existing video sequences, is essential for content creation and visual effects. However, exis…

cs.CV2026

Self Gradient Forcing: Native Long Video Extrapolation

Junhao Zhuang, Shiyi Zhang, Yuxuan Bian +11

Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-tru…

cs.CV2026

GeoEdit: Geometry-Aware Object Editing via Dual-Branch Denoising

Yi He, Jiangming Wang, Xinyu Wang +5

Precisely manipulating objects in a single photograph (translation, rotation, scaling) while obeying 3D physical constraints remains unsolved for diffusion-based editors. Current 2…

cs.CV2026

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions

Xin Lu, Luxury, Jie Huang +27

While recent autoregressive video diffusion models achieve remarkable streaming quality, they remain confined to low resolutions (e.g., 480P), leaving efficient, scalable, real-tim…

cs.CV2026

Echo-Memory: A Controlled Study of Memory in Action World Models

Wayne King, Zeyue Xue, Yuxuan Bian +13

We present \textbf{Echo-Memory}, a controlled study of memory mechanisms in action-conditioned world models. These models generate multi-segment videos from a first frame, text pro…

cs.CV2026

Astrolabe: Steering Forward-Process Reinforcement Learning for Distilled Autoregressive Video Models

Songchun Zhang, Zeyue Xue, Siming Fu +6

Distilled autoregressive (AR) video models enable efficient streaming generation but frequently misalign with human visual preferences. Existing reinforcement learning (RL) framewo…

cs.CV2026

Risk-Controllable Multi-View Diffusion for Driving Scenario Generation

Hongyi Lin, Wenxiu Shi, Heye Huang +5

Generating safety-critical driving scenarios is crucial for evaluating and improving autonomous driving systems, but long-tail risky situations are rarely observed in real-world da…

cs.CV2026

ShotVerse: Advancing Cinematic Camera Control for Text-Driven Multi-Shot Video Creation

Songlin Yang, Zhe Wang, Xuyi Yang +7

Text-driven video generation has democratized film creation, but camera control in cinematic multi-shot scenarios remains a significant block. Implicit textual prompts lack precisi…