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From the 1 of 23 linked papers with an AI index.

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20242026
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cs.CV2026

LoSA: Near-Lossless Sparse Attention for Training-Free Video Diffusion Acceleration

Enhuai Liu, Yunke Wang, Yutong Wang +2

Video diffusion transformers are costly to sample: every denoising step applies self-attention over a long 3D token sequence, a quadratic cost that dominates as resolution and dura…

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

Early Semantic Grounding in Image Editing Models for Zero-Shot Referring Image Segmentation

Jingxuan He, Xiyu Wang, Yunke Wang +2

Instruction-based image editing (IIE) models have recently demonstrated strong capability in modifying specific image regions according to natural language instructions, which impl…

cs.CV2026

Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation

Chenyu Hui, Xiaodi Huang, Siyu Xu +5

Vision-language-action (VLA) models typically rely on large-scale real-world videos, whereas simulated data, despite being inexpensive and highly parallelizable to collect, often s…

cs.CV2026

Rethinking Where to Edit: Task-Aware Localization for Instruction-Based Image Editing

Jingxuan He, Xiyu Wang, Mengyu Zheng +3

Instruction-based image editing (IIE) aims to modify images according to textual instructions while preserving irrelevant content. Despite recent advances in diffusion transformers…