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Synthesizing extrapolated views remains a difficult task, especially in urban driving scenes, where the only reliable sources of data are limited RGB captures and sparse LiDAR points. To address this problem, we present PointmapDiff, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Thang-Anh-Quan Nguyen , Nathan Piasco , Luis Roldão , Moussab Bennehar , Dzmitry Tsishkou , Laurent Caraffa , Jean-Philippe Tarel , Roland Brémond

We propose 4Real-Video, a novel framework for generating 4D videos, organized as a grid of video frames with both time and viewpoint axes. In this grid, each row contains frames sharing the same timestep, while each column contains frames…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Chaoyang Wang , Peiye Zhuang , Tuan Duc Ngo , Willi Menapace , Aliaksandr Siarohin , Michael Vasilkovsky , Ivan Skorokhodov , Sergey Tulyakov , Peter Wonka , Hsin-Ying Lee

This paper presents a new dataset for Novel View Synthesis, generated from a high-quality, animated film with stunning realism and intricate detail. Our dataset captures a variety of dynamic scenes, complete with detailed textures,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Michal Nazarczuk , Thomas Tanay , Arthur Moreau , Zhensong Zhang , Eduardo Pérez-Pellitero

Vision-centric autonomous driving has demonstrated excellent performance with economical sensors. As the fundamental step, 3D perception aims to infer 3D information from 2D images based on 3D-2D projection. This makes driving perception…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Ye Li , Wenzhao Zheng , Xiaonan Huang , Kurt Keutzer

Diffusion models currently achieve state-of-the-art performance for both conditional and unconditional image generation. However, so far, image diffusion models do not support tasks required for 3D understanding, such as view-consistent 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Titas Anciukevičius , Zexiang Xu , Matthew Fisher , Paul Henderson , Hakan Bilen , Niloy J. Mitra , Paul Guerrero

While modern diffusion models excel at generating high-quality and diverse images, they still struggle with high-fidelity compositional and multimodal control, particularly when users simultaneously specify text prompts, subject references,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yusuf Dalva , Guocheng Gordon Qian , Maya Goldenberg , Tsai-Shien Chen , Kfir Aberman , Sergey Tulyakov , Pinar Yanardag , Kuan-Chieh Jackson Wang

Live-streaming Novel View Synthesis (NVS) from unposed multi-view video remains an open challenge in a wide range of applications. Existing methods for dynamic scene representation typically require ground-truth camera parameters and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Pedro Quesado , Erkut Akdag , Yasaman Kashefbahrami , Willem Menu , Egor Bondarev

Recent advancements in diffusion and flow models have greatly improved text-based image editing, yet methods that edit images independently often produce geometrically and photometrically inconsistent results across different views of the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Josef Bengtson , David Nilsson , Dong In Lee , Yaroslava Lochman , Fredrik Kahl

Novel View Synthesis (NVS), which tries to produce a realistic image at the target view given source view images and their corresponding poses, is a fundamental problem in 3D Vision. As this task is heavily under-constrained, some recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Shijie Li , Farhad G. Zanjani , Haitam Ben Yahia , Yuki M. Asano , Juergen Gall , Amirhossein Habibian

We introduce a novel geometry-guided online video view synthesis method with enhanced view and temporal consistency. Traditional approaches achieve high-quality synthesis from dense multi-view camera setups but require significant…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Hyunho Ha , Lei Xiao , Christian Richardt , Thu Nguyen-Phuoc , Changil Kim , Min H. Kim , Douglas Lanman , Numair Khan

In recent years, video generation has seen significant advancements. However, challenges still persist in generating complex motions and interactions. To address these challenges, we introduce ReVision, a plug-and-play framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Qihao Liu , Ju He , Qihang Yu , Liang-Chieh Chen , Alan Yuille

Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffusion show promise in navigating these goals, especially when…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Can Qin , Shu Zhang , Ning Yu , Yihao Feng , Xinyi Yang , Yingbo Zhou , Huan Wang , Juan Carlos Niebles , Caiming Xiong , Silvio Savarese , Stefano Ermon , Yun Fu , Ran Xu

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control over the generated content. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Michal Geyer , Omer Bar-Tal , Shai Bagon , Tali Dekel

Diffusion Transformer has demonstrated powerful capability and scalability in generating high-quality images and videos. Further pursuing the unification of generation and editing tasks has yielded significant progress in the domain of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zeyinzi Jiang , Zhen Han , Chaojie Mao , Jingfeng Zhang , Yulin Pan , Yu Liu

Text-based 2D diffusion models have demonstrated impressive capabilities in image generation and editing. Meanwhile, the 2D diffusion models also exhibit substantial potentials for 3D editing tasks. However, how to achieve consistent edits…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Ruihuang Li , Liyi Chen , Zhengqiang Zhang , Varun Jampani , Vishal M. Patel , Lei Zhang

Hand motion plays a central role in human interaction, yet modeling realistic 4D hand motion (i.e., 3D hand pose sequences over time) remains challenging. Research in this area is typically divided into two tasks: (1) Estimation approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Zhihao Sun , Tong Wu , Ruirui Tu , Daoguo Dong , Zuxuan Wu

Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper, we propose leveraging multi-view depth, which represents…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zhen Wang , Qiangeng Xu , Feitong Tan , Menglei Chai , Shichen Liu , Rohit Pandey , Sean Fanello , Achuta Kadambi , Yinda Zhang

Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth. The new mechanism demonstrates great advantages…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Bo Zhang , Yuqi Han , Jinli Suo , Qionghai Dai

High resolution panoramic video content is paramount for immersive experiences in Virtual Reality, but is non-trivial to collect as it requires specialized equipment and intricate camera setups. In this work, we introduce VideoPanda, a…

Recent advances in diffusion-based video generation have opened new possibilities for controllable video editing, yet realistic video object insertion (VOI) remains challenging due to limited 4D scene understanding and inadequate handling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Hoiyeong Jin , Hyojin Jang , Jeongho Kim , Junha Hyung , Kinam Kim , Dongjin Kim , Huijin Choi , Hyeonji Kim , Jaegul Choo