ViBiDSampler: Enhancing Video Interpolation Using Bidirectional Diffusion Sampler
Serin Yang, Taesung Kwon, Jong Chul Ye
2025年份
8顶会引用
摘要
Figure 1: Keyframe interpolation results using our ViBiDSampler. (a) The images in the first and last rows are keyframes, and the intermediate frames are generated using ViBiDSampler. (b) A comparison of results with three baseline methods-FILM, TRF, and Generative Inbetweening (GI)-demonstrates that these baselines exhibit artifacts or unnatural appearances. In contrast, our method generates clear and realistic frames.
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引用它的顶会 Paper8
- Controllable Human-centric Keyframe Interpolation with Generative PriorZujin Guo, Size Wu, Zhongang Cai, Wei Li 等NeurIPS 2025 · 被引用 6 次
- Motion Prior Distillation in Time Reversal Sampling for Generative InbetweeningWooseok Jeon, Seunghyun Shin, Dongmin Shin, Hae-Gon JeonICLR 2026 · 被引用 5 次
- Anchoring and Rescaling Attention for Semantically Coherent InbetweeningTae Eun Choi, Sumin Shim, Junhyeok Kim, Seong Jae HwangCVPR 2026 · 被引用 2 次
- Ego-InBetween: Generating Object State Transitions in Ego-Centric VideosMengmeng Ge, Takashi Isobe, Xu Jia, Yanan Sun 等CVPR 2026 · 被引用 1 次
- TLB-VFI: Temporal-Aware Latent Brownian Bridge Diffusion for Video Frame InterpolationZonglin Lyu, Chen ChenICCV 2025 · 被引用 1 次
它引用的顶会 Paper20
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
- SDXL: Improving Latent Diffusion Models for High-Resolution Image SynthesisDustin Podell, Zion English, Kyle Lacey, Andreas Blattmann 等ICLR 2024 · 被引用 4,569 次
- Elucidating the Design Space of Diffusion-Based Generative ModelsTero Karras, Miika Aittala, Timo Aila, Samuli LaineNeurIPS 2022 · 被引用 3,959 次
- Video Diffusion ModelsJonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan 等NeurIPS 2022 · 被引用 2,948 次
- Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video GenerationJay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei 等ICCV 2023 · 被引用 1,113 次
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