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Text-to-video diffusion models have advanced video generation significantly. However, customizing these models to generate videos with tailored motions presents a substantial challenge. In specific, they encounter hurdles in (a) accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Hyeonho Jeong , Geon Yeong Park , Jong Chul Ye

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Image view synthesis has seen great success in reconstructing photorealistic visuals, thanks to deep learning and various novel representations. The next key step in immersive virtual experiences is view synthesis of dynamic scenes.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Kai-En Lin , Guowei Yang , Lei Xiao , Feng Liu , Ravi Ramamoorthi

Generating long videos that can show complex stories, like movie scenes from scripts, has great promise and offers much more than short clips. However, current methods that use autoregression with diffusion models often struggle because…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Guangcong Zheng , Jianlong Yuan , Bo Wang , Haoyang Huang , Guoqing Ma , Nan Duan

We propose a learning-based approach for novel view synthesis for multi-camera 360$^{\circ}$ panorama capture rigs. Previous work constructs RGBD panoramas from such data, allowing for view synthesis with small amounts of translation, but…

Computer Vision and Pattern Recognition · Computer Science 2020-08-06 Kai-En Lin , Zexiang Xu , Ben Mildenhall , Pratul P. Srinivasan , Yannick Hold-Geoffroy , Stephen DiVerdi , Qi Sun , Kalyan Sunkavalli , Ravi Ramamoorthi

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Video inpainting is the task of filling a region in a video in a visually convincing manner. It is very challenging due to the high dimensionality of the data and the temporal consistency required for obtaining convincing results. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Nicolas Cherel , Andrés Almansa , Yann Gousseau , Alasdair Newson

Dynamic Novel View Synthesis aims to generate photorealistic views of moving subjects from arbitrary viewpoints. This task is particularly challenging when relying on monocular video, where disentangling structure from motion is ill-posed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Michal Nazarczuk , Sibi Catley-Chandar , Thomas Tanay , Zhensong Zhang , Gregory Slabaugh , Eduardo Pérez-Pellitero

The recent innovations and breakthroughs in diffusion models have significantly expanded the possibilities of generating high-quality videos for the given prompts. Most existing works tackle the single-scene scenario with only one video…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Fuchen Long , Zhaofan Qiu , Ting Yao , Tao Mei

Current state-of-the-art methods for video inpainting typically rely on optical flow or attention-based approaches to inpaint masked regions by propagating visual information across frames. While such approaches have led to significant…

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei

Creating novel images by fusing visual cues from multiple sources is a fundamental yet underexplored problem in image-to-image generation, with broad applications in artistic creation, virtual reality and visual media. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Zeren Xiong , Yue Yu , Zedong Zhang , Shuo Chen , Jian Yang , Jun Li

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos using a base video generation model and a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Jonathan Ho , William Chan , Chitwan Saharia , Jay Whang , Ruiqi Gao , Alexey Gritsenko , Diederik P. Kingma , Ben Poole , Mohammad Norouzi , David J. Fleet , Tim Salimans

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constraints that remain challenging for perspective video generators due to their limited field of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Ting-Hsuan Chen , Ying-Huan Chen , Tao Tu , Jie-Ying Lee , Cho-Ying Wu , Fangzhou Lin , Hengyuan Zhang , David Paz , Xinyu Huang , Yuliang Guo , Yu-Lun Liu , Yue Wang , Liu Ren

Diffusion-based approaches have recently demonstrated strong performance for single-image novel view synthesis by conditioning generative models on geometry inferred from monocular depth estimation. However, in practice, the quality and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Amirhosein Javadi , Chi-Shiang Gau , Konstantinos D. Polyzos , Tara Javidi

Novel-view synthesis through diffusion models has demonstrated remarkable potential for generating diverse and high-quality images. Yet, the independent process of image generation in these prevailing methods leads to challenges in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-01 Xianghui Yang , Yan Zuo , Sameera Ramasinghe , Loris Bazzani , Gil Avraham , Anton van den Hengel

Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing methods predominantly focus on camera control in perspective projection video generation, while…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Chenhao Ji , Chaohui Yu , Junyao Gao , Fan Wang , Cairong Zhao