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From the 2 of 71 linked papers with an AI index.

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20242026
most citedGameFactory: Creating New Games with Generative Interactive Videos

1 citations · 1 across the 20 of their papers we have counts for

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cs.CV2026

MAVIN: Multi-Shot Audio-Visual Generation with Customized Narrative Control

Kaiqi Liu, Yunyao Mao, Ziqi Cai +8

MAVIN is a framework for generating multi-shot audio‑visual content with fine‑grained narrative control, using boundary‑aware attention to align temporal segments and ID‑aware prop…

cs.CV2026

UniVideo: Unified Understanding, Generation, and Editing for Videos

Cong Wei, Quande Liu, Zixuan Ye +5

Unified multimodal models have shown promising results in multimodal content generation and editing but remain largely limited to the image domain. In this work, we present UniVide…

cs.CV2026

HandsOnWorld: Unconstrained Egocentric Video Generation with Camera-Disentangled Hand Control

Yushuo Chen, Xiaoyu Shi, Xiaoshi Wu +3

We present HandsOnWorld, a framework for hand-controlled egocentric video generation that learns directly from unconstrained monocular video. Prior generators depend on 3D hand ann…

cs.CV2026

AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization

Yu Li, Menghan Xia, Gongye Liu +8

Despite being a pivotal frontier, interactive world modeling remains underexplored in terms of the versatile controllability required by practical scenarios. To bridge this gap, we…

cs.CV2026

VideoCanvas: Unified Video Completion from Arbitrary Spatiotemporal Patches via In-Context Conditioning

Minghong Cai, Qiulin Wang, Zongli Ye +7

Existing controllable video generation methods are typically designed for rigid, task-specific settings, such as first-frame image-to-video, inpainting, or interpolation, treating…

cs.CV2026

Latent Diffusion Model without Variational Autoencoder

Minglei Shi, Haolin Wang, Wenzhao Zheng +6

Recent progress in diffusion-based visual generation has largely relied on latent diffusion models with variational autoencoders (VAEs). While effective for high-fidelity synthesis…