mlsanityData to 14 Oct 2026

Framer: Interactive Frame Interpolation

arXiv 2410.18978 ↗First posted 24 Oct 2024cs.CVcited by 24

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Abstract (arXiv)

We propose Framer for interactive frame interpolation, which targets producing smoothly transitioning frames between two images as per user creativity. Concretely, besides taking the start and end frames as inputs, our approach supports customizing the transition process by tailoring the trajectory of some selected keypoints. Such a design enjoys two clear benefits. First, incorporating human interaction mitigates the issue arising from numerous possibilities of transforming one image to another, and in turn enables finer control of local motions. Second, as the most basic form of interaction, keypoints help establish the correspondence across frames, enhancing the model to handle challenging cases (e.g., objects on the start and end frames are of different shapes and styles). It is noteworthy that our system also offers an "autopilot" mode, where we introduce a module to estimate the keypoints and refine the trajectory automatically, to simplify the usage in practice. Extensive experimental results demonstrate the appealing performance of Framer on various applications, such as image morphing, time-lapse video generation, cartoon interpolation, etc. The code, the model, and the interface will be released to facilitate further research.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). Builds on 52 of its 60 references that are in the map. First posted on arXiv 24 Oct 2024.

Builds on

52 of 60 references.

References · 52

  1. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  2. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
  3. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,476
  4. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,351
  5. 2017The 2017 DAVIS Challenge on Video Object Segmentationcited by 957
  6. 2024WorldSimBench: Towards Video Generation Models as World Simulatorscited by 881
  7. 2023ModelScope Text-to-Video Technical Reportcited by 658
  8. 2017Video Enhancement with Task-Oriented Flowcited by 619
  9. 2023MotionCtrl: A Unified and Flexible Motion Controller for Video Generationcited by 580
  10. 2024VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Modelscited by 579
  11. 2023VideoCrafter1: Open Diffusion Models for High-Quality Video Generationcited by 535
  12. 2023CoTracker: It is Better to Track Togethercited by 522
38 more
  1. 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 471
  2. 2023VideoComposer: Compositional Video Synthesis with Motion Controllabilitycited by 464
  3. 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generationcited by 460
  4. 2024OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generationcited by 341
  5. 2017Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolationcited by 326
  6. 2023DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editingcited by 294
  7. 2023Preserve Your Own Correlation: A Noise Prior for Video Diffusion Modelscited by 285
  8. 2020Softmax Splatting for Video Frame Interpolationcited by 279
  9. 2023DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectorycited by 264
  10. 2019Depth-Aware Video Frame Interpolationcited by 234
  11. 2023Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifoldcited by 219
  12. 2017Video Frame Interpolation via Adaptive Separable Convolutioncited by 213
  13. 2023AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolationcited by 180
  14. 2023SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Modelscited by 175
  15. 2024DragAnything: Motion Control for Anything using Entity Representationcited by 159
  16. 2024VD3D: Taming Large Video Diffusion Transformers for 3D Camera Controlcited by 156
  17. 2018Context-aware Synthesis for Video Frame Interpolationcited by 153
  18. 2022FILM: Frame Interpolation for Large Motioncited by 153
  19. 2019Quadratic video interpolationcited by 145
  20. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Pathscited by 142
  21. 2019AdaCoF: Adaptive Collaboration of Flows for Video Frame Interpolationcited by 134
  22. 2021XVFI: eXtreme Video Frame Interpolationcited by 126
  23. 2021Video Frame Interpolation Transformercited by 123
  24. 2020BMBC:Bilateral Motion Estimation with Bilateral Cost Volume for Video Interpolationcited by 118
  25. 2018MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancementcited by 112
  26. 2022IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolationcited by 109
  27. 2021Asymmetric Bilateral Motion Estimation for Video Frame Interpolationcited by 101
  28. 2020FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolationcited by 98
  29. 2023LDMVFI: Video Frame Interpolation with Latent Diffusion Modelscited by 89
  30. 2024ReVideo: Remake a Video with Motion and Content Controlcited by 74
  31. 2024Video Interpolation with Diffusion Modelscited by 68
  32. 2024ToonCrafter: Generative Cartoon Interpolationcited by 68
  33. 2020Multiple Video Frame Interpolation via Enhanced Deformable Separable Convolutioncited by 63
  34. 2021CDFI: Compression-Driven Network Design for Frame Interpolationcited by 56
  35. 2020Enhanced Quadratic Video Interpolationcited by 48
  36. 2024Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolationcited by 44
  37. 2021ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolationcited by 35
  38. 2024Explorative Inbetweening of Time and Spacecited by 21

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 18; 2026: 4.

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  1. 2025DICEPTION: A Generalist Diffusion Model for Visual Perceptual Taskscited by 39
  2. 2024Generative Inbetweening through Frame-wise Conditions-Driven Video Generationcited by 24
  3. 2025Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interactioncited by 13
  4. 2025LayerAnimate: Layer-level Control for Animationcited by 12
  5. 2025AceVFI: A Comprehensive Survey of Advances in Video Frame Interpolationcited by 9
  6. 2025LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Modelcited by 9
  7. 2025Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimizationcited by 9
  8. 2025QuaDreamer: Controllable Panoramic Video Generation for Quadruped Robotscited by 8
  9. 2025In-2-4D: Inbetweening from Two Single-View Images to 4D Generationcited by 7
  10. 2026Motion Prior Distillation in Time Reversal Sampling for Generative Inbetweeningcited by 6
  11. 2025EF-VI: Enhancing End-Frame Injection for Video Inbetweeningcited by 4
  12. 2025EventDiff: A Unified and Efficient Diffusion Model Framework for Event-based Video Frame Interpolationcited by 3
12 more
  1. 2025FakeParts: a New Family of AI-Generated DeepFakescited by 3
  2. 2025MultiCOIN: Multi-Modal COntrollable Video INbetweeningcited by 2
  3. 2026SPLIT: Training-Free AI-Generated and Partially Edited Video Detection via Spatial Patch-Level Incoherence and Temporal Roughnesscited by 2
  4. 2024Adapting Image-to-Video Diffusion Models for Large-Motion Frame Interpolationcited by 1
  5. 2025Semantic Frame Interpolationcited by 1
  6. 2025Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Qualitycited by 1
  7. 2025CineLOG: A Training Free Approach for Cinematic Long Video Generationcited by 1
  8. 2026Can Video Diffusion Models Predict Past Frames? Bidirectional Cycle Consistency for Reversible Interpolationcited by 1
  9. 2025How Animals Dance (When You're Not Looking)cited by 0
  10. 2025D3-Predictor: Noise-Free Deterministic Diffusion for Dense Predictioncited by 0
  11. 2025A Study of the Design Space of Motion and Disocclusion Control in Video Generationcited by 0
  12. 2026FC-VFI: Faithful and Consistent Video Frame Interpolation for High-FPS Slow Motion Video Generationcited by 0