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Recent attempts to solve the problem of head reenactment using a single reference image have shown promising results. However, most of them either perform poorly in terms of photo-realism, or fail to meet the identity preservation problem,…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Michail Christos Doukas , Stefanos Zafeiriou , Viktoriia Sharmanska

We introduce X-Ray, a novel 3D sequential representation inspired by the penetrability of x-ray scans. X-Ray transforms a 3D object into a series of surface frames at different layers, making it suitable for generating 3D models from…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Tao Hu , Wenhang Ge , Yuyang Zhao , Gim Hee Lee

We introduce VividDream, a method for generating explorable 4D scenes with ambient dynamics from a single input image or text prompt. VividDream first expands an input image into a static 3D point cloud through iterative inpainting and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yao-Chih Lee , Yi-Ting Chen , Andrew Wang , Ting-Hsuan Liao , Brandon Y. Feng , Jia-Bin Huang

We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors. Unlike previous methods that either iteratively warp 2D views onto a mesh…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Dave Zhenyu Chen , Haoxuan Li , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

In this paper we propose a neural message passing approach to augment an input 3D indoor scene with new objects matching their surroundings. Given an input, potentially incomplete, 3D scene and a query location, our method predicts a…

Computer Vision and Pattern Recognition · Computer Science 2019-07-29 Yang Zhou , Zachary While , Evangelos Kalogerakis

Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretrained state-of-the-art generation models, guided by 2D layout…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yishen Ji , Ziyue Zhu , Zhenxin Zhu , Kaixin Xiong , Ming Lu , Zhiqi Li , Lijun Zhou , Haiyang Sun , Bing Wang , Tong Lu

While recent advances in neural representations and generative models have revolutionized 3D content creation, the field remains constrained by significant data processing bottlenecks. To address this, we introduce HY3D-Bench, an…

The significant progress on Generative Adversarial Networks (GANs) have made it possible to generate surprisingly realistic images for single object based on natural language descriptions. However, controlled generation of images for…

Computer Vision and Pattern Recognition · Computer Science 2019-11-14 Hongdong Zheng , Yalong Bai , Wei Zhang , Tao Mei

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

In this paper, we tackle a new task of 3D object synthesis, where a 3D model is composited with another object category to create a novel 3D model. However, most existing text/image/3D-to-3D methods struggle to effectively integrate…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zeren Xiong , Zikun Chen , Zedong Zhang , Xiang Li , Ying Tai , Jian Yang , Jun Li

We introduce MG-Gen, a framework that generates motion graphics directly from a single raster image. MG-Gen decompose a single raster image into layered structures represented as HTML, generate animation scripts for each layer, and then…

Graphics · Computer Science 2025-07-15 Takahiro Shirakawa , Tomoyuki Suzuki , Takuto Narumoto , Daichi Haraguchi

We present SceneTok, a novel tokenizer for encoding view sets of scenes into a compressed and diffusable set of unstructured tokens. Existing approaches for 3D scene representation and generation commonly use 3D data structures or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Mohammad Asim , Christopher Wewer , Jan Eric Lenssen

Directly generating scenes from satellite imagery offers exciting possibilities for integration into applications like games and map services. However, challenges arise from significant view changes and scene scale. Previous efforts mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zuoyue Li , Zhenqiang Li , Zhaopeng Cui , Marc Pollefeys , Martin R. Oswald

We present SIGMA-GEN, a unified framework for multi-identity preserving image generation. Unlike prior approaches, SIGMA-GEN is the first to enable single-pass multi-subject identity-preserved generation guided by both structural and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Oindrila Saha , Vojtech Krs , Radomir Mech , Subhransu Maji , Kevin Blackburn-Matzen , Matheus Gadelha

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

This study aims to investigate the challenge of insufficient three-dimensional context in synthetic datasets for scene text rendering. Although recent advances in diffusion models and related techniques have improved certain aspects of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Li-Syun Hsiung , Jun-Kai Tu , Kuan-Wu Chu , Yu-Hsuan Chiu , Yan-Tsung Peng , Sheng-Luen Chung , Gee-Sern Jison Hsu

We introduce SceneLinker, a novel framework that generates compositional 3D scenes via semantic scene graph from RGB sequences. To adaptively experience Mixed Reality (MR) content based on each user's space, it is essential to generate a 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Seok-Young Kim , Dooyoung Kim , Woojin Cho , Hail Song , Suji Kang , Woontack Woo

We present CineVerse, a novel framework for the task of cinematic scene composition. Similar to traditional multi-shot generation, our task emphasizes the need for consistency and continuity across frames. However, our task also focuses on…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Quynh Phung , Long Mai , Fabian David Caba Heilbron , Feng Liu , Jia-Bin Huang , Cusuh Ham

We tackle the challenge of generating the infinitely extendable 3D world -- large, continuous environments with coherent geometry and realistic appearance. Existing methods face key challenges: 2D-lifting approaches suffer from geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Sikuang Li , Chen Yang , Jiemin Fang , Taoran Yi , Jia Lu , Jiazhong Cen , Lingxi Xie , Wei Shen , Qi Tian

Current compositional image-to-3D scene generation approaches construct 3D scenes by time-consuming iterative layout optimization or inflexible joint object-layout generation. Moreover, most methods rely on limited field-of-view perspective…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zidian Qiu , Ancong Wu
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