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20242026
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cs.CV2026

Motion Attribution for Video Generation

Xindi Wu, Despoina Paschalidou, Jun Gao +5

Despite the rapid progress of video generation models, the role of data in influencing motion is poorly understood. We present Motive (MOTIon attribution for Video gEneration), a m…

cs.CV2026

VideoSketcher: Sequential Sketch Generation Using Video Model Priors

Hui Ren, Yuval Alaluf, Omer Bar Tal +3

Sketching is inherently sequential: strokes are drawn progressively to explore and refine ideas. Yet most generative approaches treat sketches as static images, ignoring the tempor…

cs.CV2026

Tensor Memory: Fixed-Size Recurrent State for Long-Horizon Transformers

Kabir Swain, Sijie Han, Daniel Karl I. Weidele +2

Transformers process images and videos by flattening space and time into long token sequences. While attention and KV caching preserve past features, their memory grows with sequen…

cs.CV2026

Vision-Language Binding in In-Context Image Generation

Chris Ge, Rohit Gandikota, Antonio Torralba +1

In-context image generation models such as FLUX.2 take a text prompt and an optional reference image as visual conditioning for the output. Internally, all three inputs -- text, re…

cs.CV2025

Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos

Hanxue Liang, Jiawei Ren, Ashkan Mirzaei +8

Recent advancements in static feed-forward scene reconstruction have demonstrated significant progress in high-quality novel view synthesis. However, these models often struggle wi…