AKiRa: Augmentation Kit on Rays for optical video generation
On the map: Diffusion models → Video generation
Abstract (arXiv)
Recent advances in text-conditioned video diffusion have greatly improved video quality. However, these methods offer limited or sometimes no control to users on camera aspects, including dynamic camera motion, zoom, distorted lens and focus shifts. These motion and optical aspects are crucial for adding controllability and cinematic elements to generation frameworks, ultimately resulting in visual content that draws focus, enhances mood, and guides emotions according to filmmakers' controls. In this paper, we aim to close the gap between controllable video generation and camera optics. To achieve this, we propose AKiRa (Augmentation Kit on Rays), a novel augmentation framework that builds and trains a camera adapter with a complex camera model over an existing video generation backbone. It enables fine-tuned control over camera motion as well as complex optical parameters (focal length, distortion, aperture) to achieve cinematic effects such as zoom, fisheye effect, and bokeh. Extensive experiments demonstrate AKiRa's effectiveness in combining and composing camera optics while outperforming all state-of-the-art methods. This work sets a new landmark in controlled and optically enhanced video generation, paving the way for future optical video generation methods.
Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Placed in Video generation, one of 14 directions in Diffusion models. Builds on 51 of its 77 references that are in the map. First posted on arXiv 18 Dec 2024.
Builds on
51 of 77 references.
Closest ancestors · 18
Same direction, newest first
- 2024CamI2V: Camera-Controlled Image-to-Video Diffusion Model21 Oct
- 2024Boosting Camera Motion Control for Video Diffusion Transformers14 Oct
- 2024VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control17 Jul
- 2024CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation4 Jun
- 2024MotionMaster: Training-free Camera Motion Transfer For Video Generation24 Apr
- 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generation2 Apr
- 2024Cinematographic Camera Diffusion Model25 Feb
- 2024Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motion5 Feb
- 2024Latte: Latent Diffusion Transformer for Video Generation5 Jan
- 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets25 Nov
- 2023VideoCrafter1: Open Diffusion Models for High-Quality Video Generation30 Oct
- 2023LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models26 Sep
6 more
- 2023ModelScope Text-to-Video Technical Report12 Aug
- 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning10 Jul
- 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models18 Apr
- 2023Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generation17 Apr
- 2022Imagen Video: High Definition Video Generation with Diffusion Models5 Oct
- 2022Video Diffusion Models7 Apr
Other references · 33
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
- 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
- 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,415
- 2023VBench: Comprehensive Benchmark Suite for Video Generative Modelscited by 1,822
- 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,742
- 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,464
- 2024Depth Anything V2cited by 1,422
- 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,234
21 more
- 2021Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrievalcited by 1,177
- 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,043
- 2016Conditional Image Generation with PixelCNN Decoderscited by 862
- 2024Movie Gen: A Cast of Media Foundation Modelscited by 644
- 2023MotionCtrl: A Unified and Flexible Motion Controller for Video Generationcited by 580
- 2023VideoComposer: Compositional Video Synthesis with Motion Controllabilitycited by 464
- 2024Global Structure-from-Motion Revisitedcited by 218
- 2024Cameras as Rays: Pose Estimation via Ray Diffusioncited by 131
- 2024Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesiscited by 105
- 2024MotionBooth: Motion-Aware Customized Text-to-Video Generationcited by 93
- 2022ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wildcited by 92
- 2024HumanVid: Demystifying Training Data for Camera-controllable Human Image Animationcited by 64
- 2022Efficient Video Prediction via Sparsely Conditioned Flow Matchingcited by 55
- 2022BokehMe: When Neural Rendering Meets Classical Renderingcited by 48
- 2020FlowFusion: Dynamic Dense RGB-D SLAM Based on Optical Flowcited by 37
- 2024E.T. the Exceptional Trajectories: Text-to-camera-trajectory generation with character awarenesscited by 25
- 2024Beyond FVD: Enhanced Evaluation Metrics for Video Generation Qualitycited by 22
- 2023JAWS: Just A Wild Shot for Cinematic Transfer in Neural Radiance Fieldscited by 13
- 2023Cinematic Behavior Transfer via NeRF-based Differentiable Filmingcited by 12
- 2022SCAM! Transferring humans between images with Semantic Cross Attention Modulationcited by 10
- 2024DreamCinema: Cinematic Transfer with Free Camera and 3D Charactercited by 9
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Citing papers per year: 2025: 10; 2026: 8.
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- 2026VIGOR: VIdeo Geometry-Oriented Reward for Temporal Generative Alignment17 Mar 2026
- 2026Diffusion Reinforcement Learning via Centered Reward Distillation14 Mar 2026
- 2026Focal Guidance: Unlocking Controllability from Semantic-Weak Layers in Video Diffusion Models12 Jan 2026
- 2026DreamLoop: Controllable Cinemagraph Generation from a Single Photograph6 Jan 2026
- 2025What about gravity in video generation? Post-Training Newton's Laws with Verifiable Rewards29 Nov 2025
- 2025One-step Diffusion Models with Bregman Density Ratio Matching19 Oct 2025
- 2025Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation23 Sep 2025
- 2025VLIPP: Towards Physically Plausible Video Generation with Vision and Language Informed Physical Prior30 Mar 2025
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- 2026SPLIT: Training-Free AI-Generated and Partially Edited Video Detection via Spatial Patch-Level Incoherence and Temporal Roughnesscited by 2
- 2025Zero-Shot Personalized Camera Motion Control for Image-to-Video Synthesiscited by 1
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- 2026DeltaCam: Differential Intrinsic Camera Modeling for Video Generationcited by 0
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- 2026SPLIT: Training-Free AI-Generated and Partially Edited Video Detection via Spatial Patch-Level Incoherence and Temporal Roughness3 Jul 2026
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- 2025Every Camera Effect, Every Time, All at Once: 4D Gaussian Ray Tracing for Physics-based Camera Effect Data Generation13 Sep 2025
- 2025FakeParts: a New Family of AI-Generated DeepFakes28 Aug 2025
- 2025Follow-Your-Creation: Empowering 4D Creation through Video Inpainting5 Jun 2025
- 2025Zero-Shot Personalized Camera Motion Control for Image-to-Video Synthesis13 Apr 2025
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