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VBench: Comprehensive benchmark suite for video generative models

3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

citation-role summary

dataset 2

citation-polarity summary

fields

cs.CV 3

years

2026 1 2025 2

verdicts

UNVERDICTED 3

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dataset 2

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use dataset 2

representative citing papers

SkyReels-V2: Infinite-length Film Generative Model

cs.CV · 2025-04-17 · unverdicted · novelty 6.0

SkyReels-V2 produces infinite-length film videos via MLLM-based captioning, progressive pretraining, motion RL, and diffusion forcing with non-decreasing noise schedules.

Motif-Video 2B: Technical Report

cs.CV · 2026-04-14 · unverdicted · novelty 4.0 · 2 refs

Motif-Video 2B reaches 83.76% on VBench, outperforming a 14B-parameter model with 7x fewer parameters and far less training data through shared cross-attention and a three-part backbone.

citing papers explorer

Showing 3 of 3 citing papers.

  • SkyReels-V2: Infinite-length Film Generative Model cs.CV · 2025-04-17 · unverdicted · none · ref 6

    SkyReels-V2 produces infinite-length film videos via MLLM-based captioning, progressive pretraining, motion RL, and diffusion forcing with non-decreasing noise schedules.

  • SynMotion: Semantic-Visual Adaptation for Motion Customized Video Generation cs.CV · 2025-06-30 · unverdicted · none · ref 33

    SynMotion combines disentangled semantic embeddings, parameter-efficient motion adapters, and alternate subject-motion training on a new SPV dataset to improve motion customization in text-to-video and image-to-video generation.

  • Motif-Video 2B: Technical Report cs.CV · 2026-04-14 · unverdicted · none · ref 15 · 2 links

    Motif-Video 2B reaches 83.76% on VBench, outperforming a 14B-parameter model with 7x fewer parameters and far less training data through shared cross-attention and a three-part backbone.