most citedA Mechanistic View on Video Generation as World Models: State and Dynamics

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cs.CV2026

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs

Haojian Huang, Harold Haodong Chen, Meng Luo +6

We introduce VidPair-Halluc, a new benchmark for evaluating video hallucination in large video models (LVMs) under rigorous and controlled conditions. Unlike previous benchmarks th…

cs.CV2026

LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation

Yukang Chen, Luozhou Wang, Wei Huang +13

We present LongLive-2.0, an NVFP4-based parallel infrastructure throughout the full training and inference workflow of long video generation, addressing speed and memory bottleneck…

cs.CV2026

Focusable Monocular Depth Estimation

Yuxin Du, Tao Lin, Zile Zhong +7

Monocular depth foundation models generalize well across scenes, yet they are typically optimized with uniform pixel-wise objectives that do not distinguish user-specified or task-…

cs.CV2026

RectifiedHR: Enable Efficient High-Resolution Synthesis via Energy Rectification

Zhen Yang, Guibao Shen, Minyang Li +5

Diffusion models have achieved remarkable progress across various visual generation tasks. However, their performance significantly declines when generating content at resolutions…

cs.CV20261 cited

A Mechanistic View on Video Generation as World Models: State and Dynamics

Luozhou Wang, Zhifei Chen, Yihua Du +11

Large-scale video generation models have demonstrated emergent physical coherence, positioning them as potential world models. However, a gap remains between contemporary "stateles…

cs.CV2026

CamPilot: Improving Camera Control in Video Diffusion Model with Efficient Camera Reward Feedback

Wenhang Ge, Guibao Shen, Jiawei Feng +5

Recent advances in camera-controlled video diffusion models have significantly improved video-camera alignment. However, the camera controllability still remains limited. In this w…