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Recently video diffusion models have emerged as expressive generative tools for high-quality video content creation readily available to general users. However, these models often do not offer precise control over camera poses for video…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Dejia Xu , Weili Nie , Chao Liu , Sifei Liu , Jan Kautz , Zhangyang Wang , Arash Vahdat

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Yi Zhou , Guillermo Gallego , Henri Rebecq , Laurent Kneip , Hongdong Li , Davide Scaramuzza

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

Recent advances in video generation have made it possible to produce visually compelling videos, with wide-ranging applications in content creation, entertainment, and virtual reality. However, most existing diffusion transformer based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Teng Hu , Jiangning Zhang , Zihan Su , Ran Yi

Modern video generative models based on diffusion models can produce very realistic clips, but they are computationally inefficient, often requiring minutes of GPU time for just a few seconds of video. This inefficiency poses a critical…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Jieying Chen , Jeffrey Hu , Joan Lasenby , Ayush Tewari

We present GEN3C, a generative video model with precise Camera Control and temporal 3D Consistency. Prior video models already generate realistic videos, but they tend to leverage little 3D information, leading to inconsistencies, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Xuanchi Ren , Tianchang Shen , Jiahui Huang , Huan Ling , Yifan Lu , Merlin Nimier-David , Thomas Müller , Alexander Keller , Sanja Fidler , Jun Gao

This paper introduces Stereo-Talker, a novel one-shot audio-driven human video synthesis system that generates 3D talking videos with precise lip synchronization, expressive body gestures, temporally consistent photo-realistic quality, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xiang Deng , Youxin Pang , Xiaochen Zhao , Chao Xu , Lizhen Wang , Hongjiang Xiao , Shi Yan , Hongwen Zhang , Yebin Liu

We introduce MultiDiff, a novel approach for consistent novel view synthesis of scenes from a single RGB image. The task of synthesizing novel views from a single reference image is highly ill-posed by nature, as there exist multiple,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Norman Müller , Katja Schwarz , Barbara Roessle , Lorenzo Porzi , Samuel Rota Bulò , Matthias Nießner , Peter Kontschieder

Scalable and reliable evaluation is increasingly critical in the end-to-end era of autonomous driving, where vision--language--action (VLA) policies directly map raw sensor streams to driving actions. Yet, current evaluation pipelines still…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Chaoda Zheng , Sean Li , Jinhao Deng , Zhennan Wang , Shijia Chen , Liqiang Xiao , Ziheng Chi , Hongbin Lin , Kangjie Chen , Boyang Wang , Yu Zhang , Xianming Liu

We introduce the WorldScore benchmark, the first unified benchmark for world generation. We decompose world generation into a sequence of next-scene generation tasks with explicit camera trajectory-based layout specifications, enabling…

Graphics · Computer Science 2025-12-02 Haoyi Duan , Hong-Xing Yu , Sirui Chen , Li Fei-Fei , Jiajun Wu

Devising intelligent agents able to live in an environment and learn by observing the surroundings is a longstanding goal of Artificial Intelligence. From a bare Machine Learning perspective, challenges arise when the agent is prevented…

Computer Vision and Pattern Recognition · Computer Science 2022-04-27 Matteo Tiezzi , Simone Marullo , Lapo Faggi , Enrico Meloni , Alessandro Betti , Stefano Melacci

We introduce \textit{ImmersePro}, an innovative framework specifically designed to transform single-view videos into stereo videos. This framework utilizes a novel dual-branch architecture comprising a disparity branch and a context branch…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Jian Shi , Zhenyu Li , Peter Wonka

Video generation has recently made striking visual progress, but maintaining coherent object motion and interactions remains difficult. We trace two practical bottlenecks: (i) human-provided motion hints (e.g., small 2D maps) often collapse…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Zhifei Chen , Tianshuo Xu , Leyi Wu , Luozhou Wang , Dongyu Yan , Zihan You , Wenting Luo , Guo Zhang , Yingcong Chen

We introduce CinemaWorld, a generative augmented reality system that augments the viewer's physical surroundings with automatically generated mixed reality 3D content extracted from and synchronized with 2D movie scenes. Our system…

Human-Computer Interaction · Computer Science 2026-03-10 Keiichi Ihara , DaeHo Lee , Manato Abe , Hye-Young Jo , Ryo Suzuki

Generating realistic images from arbitrary views based on a single source image remains a significant challenge in computer vision, with broad applications ranging from e-commerce to immersive virtual experiences. Recent advancements in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-25 Ido Sobol , Chenfeng Xu , Or Litany

Learning to understand dynamic 3D scenes from imagery is crucial for applications ranging from robotics to scene reconstruction. Yet, unlike other problems where large-scale supervised training has enabled rapid progress, directly…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Linyi Jin , Richard Tucker , Zhengqi Li , David Fouhey , Noah Snavely , Aleksander Holynski

Multi-view or 4D video generation has emerged as a significant research topic. Nonetheless, recent approaches to 4D generation still struggle with fundamental limitations, as they primarily rely on harnessing multiple video diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Jangho Park , Taesung Kwon , Jong Chul Ye

Most existing methods for category-level pose estimation rely on object point clouds. However, when considering transparent objects, depth cameras are usually not able to capture meaningful data, resulting in point clouds with severe…

Robotics · Computer Science 2022-11-04 Kai Chen , Stephen James , Congying Sui , Yun-Hui Liu , Pieter Abbeel , Qi Dou

We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with a fallback to monocular depth estimation when rectification is…