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In this work we propose a deep learning pipeline to predict the visual future appearance of an urban scene. Despite recent advances, generating the entire scene in an end-to-end fashion is still far from being achieved. Instead, here we…

Computer Vision and Pattern Recognition · Computer Science 2021-10-25 Alessandro Simoni , Luca Bergamini , Andrea Palazzi , Simone Calderara , Rita Cucchiara

In this paper, we investigate the generation of new video backgrounds given a human foreground video, a camera pose, and a reference scene image. This task presents three key challenges. First, the generated background should precisely…

The ability to synthesize long-term human motion sequences in real-world scenes can facilitate numerous applications. Previous approaches for scene-aware motion synthesis are constrained by pre-defined target objects or positions and thus…

Computer Vision and Pattern Recognition · Computer Science 2022-05-27 Jingbo Wang , Yu Rong , Jingyuan Liu , Sijie Yan , Dahua Lin , Bo Dai

Structure from motion (SfM) enables us to reconstruct a scene via casual capture from cameras at different viewpoints, and novel view synthesis (NVS) allows us to render a captured scene from a new viewpoint. Both are hard with casual…

This presentation introduces a self-supervised learning approach to the synthesis of new video clips from old ones, with several new key elements for improved spatial resolution and realism: It conditions the synthesis process on contextual…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Guillaume Le Moing , Jean Ponce , Cordelia Schmid

While text-to-image generation has been extensively studied, generating images from scene graphs remains relatively underexplored, primarily due to challenges in accurately modeling spatial relationships and object interactions. To fill…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Zuyao Chen , Jinlin Wu , Zhen Lei , Chang Wen Chen

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

The requirement of large amounts of annotated images has become one grand challenge while training deep neural network models for various visual detection and recognition tasks. This paper presents a novel image synthesis technique that…

Computer Vision and Pattern Recognition · Computer Science 2018-09-27 Fangneng Zhan , Shijian Lu , Chuhui Xue

Video storytelling is engaging multimedia content that utilizes video and its accompanying narration to attract the audience, where a key challenge is creating narrations for recorded visual scenes. Previous studies on dense video…

Multimedia · Computer Science 2024-12-31 Dingyi Yang , Chunru Zhan , Ziheng Wang , Biao Wang , Tiezheng Ge , Bo Zheng , Qin Jin

The vision-based semantic scene completion task aims to predict dense geometric and semantic 3D scene representations from 2D images. However, the presence of dynamic objects in the scene seriously affects the accuracy of the model…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Meng Wang , Fan Wu , Yunchuan Qin , Ruihui Li , Zhuo Tang , Kenli Li

Synthesizing novel views for urban environments is crucial for tasks like autonomous driving and virtual tours. Compared to object-level or indoor situations, outdoor settings present unique challenges, such as inconsistency across frames…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Mreenav Shyam Deka , Lu Sang , Daniel Cremers

Continual learning refers to the ability of humans and animals to incrementally learn over time in a given environment. Trying to simulate this learning process in machines is a challenging task, also due to the inherent difficulty in…

Computer Vision and Pattern Recognition · Computer Science 2021-09-17 Enrico Meloni , Alessandro Betti , Lapo Faggi , Simone Marullo , Matteo Tiezzi , Stefano Melacci

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Text-to-3D form plays a crucial role in creating editable 3D scenes for AR/VR. Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-trained diffusion models for text-to-3D object generation. However, one…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Haotian Bai , Yuanhuiyi Lyu , Lutao Jiang , Sijia Li , Haonan Lu , Xiaodong Lin , Lin Wang

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

Existing 4D synthesis methods primarily focus on object-level generation or dynamic scene synthesis with limited novel views, restricting their ability to generate multi-view consistent and immersive dynamic 4D scenes. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Junwei Zhou , Xueting Li , Lu Qi , Ming-Hsuan Yang

As Artificial Intelligence Generated Content (AIGC) advances, a variety of methods have been developed to generate text, images, videos, and 3D objects from single or multimodal inputs, contributing efforts to emulate human-like cognitive…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Yiying Yang , Fukun Yin , Jiayuan Fan , Xin Chen , Wanzhang Li , Gang Yu

Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applications by abstracting the scene context in a compact manner.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Guangyao Zhai , Evin Pınar Örnek , Shun-Cheng Wu , Yan Di , Federico Tombari , Nassir Navab , Benjamin Busam

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

Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Oran Gafni , Adam Polyak , Oron Ashual , Shelly Sheynin , Devi Parikh , Yaniv Taigman
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