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The advancement of text-driven 3D content editing has been blessed by the progress from 2D generative diffusion models. However, a major obstacle hindering the widespread adoption of 3D content editing is its time-intensive processing. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Liangchen Song , Liangliang Cao , Jiatao Gu , Yifan Jiang , Junsong Yuan , Hao Tang

Despite the remarkable progress in deep generative models, synthesizing high-resolution and temporally coherent videos still remains a challenge due to their high-dimensionality and complex temporal dynamics along with large spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Sihyun Yu , Kihyuk Sohn , Subin Kim , Jinwoo Shin

We introduce Reangle-A-Video, a unified framework for generating synchronized multi-view videos from a single input video. Unlike mainstream approaches that train multi-view video diffusion models on large-scale 4D datasets, our method…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Hyeonho Jeong , Suhyeon Lee , Jong Chul Ye

Latent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-resolution images. However, the iterative sampling process is computationally intensive and leads to slow generation. Inspired by Consistency Models (song…

Computer Vision and Pattern Recognition · Computer Science 2023-10-09 Simian Luo , Yiqin Tan , Longbo Huang , Jian Li , Hang Zhao

We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V). Our intuition is simple: learn what the world looks like and how it is described from…

Computer Vision and Pattern Recognition · Computer Science 2022-09-30 Uriel Singer , Adam Polyak , Thomas Hayes , Xi Yin , Jie An , Songyang Zhang , Qiyuan Hu , Harry Yang , Oron Ashual , Oran Gafni , Devi Parikh , Sonal Gupta , Yaniv Taigman

Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

In image generation, Multiple Latent Variable Generative Models (MLVGMs) employ multiple latent variables to gradually shape the final images, from global characteristics to finer and local details (e.g., StyleGAN, NVAE), emerging as…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Dario Serez , Marco Cristani , Alessio Del Bue , Vittorio Murino , Pietro Morerio

Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D generation process. In this work, we delve into the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Seungwook Kim , Yichun Shi , Kejie Li , Minsu Cho , Peng Wang

Synthesizing a novel view from a single input image is a challenging task. Traditionally, this task was approached by estimating scene depth, warping, and inpainting, with machine learning models enabling parts of the pipeline. More…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Noam Elata , Bahjat Kawar , Yaron Ostrovsky-Berman , Miriam Farber , Ron Sokolovsky

Computer-assisted interventions can improve intra-operative guidance, particularly through deep learning methods that harness the spatiotemporal information in surgical videos. However, the severe data imbalance often found in surgical…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Danush Kumar Venkatesh , Isabel Funke , Micha Pfeiffer , Fiona Kolbinger , Hanna Maria Schmeiser , Juergen Weitz , Marius Distler , Stefanie Speidel

Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampered by the challenge of maintaining temporal consistency…

Computer Vision and Pattern Recognition · Computer Science 2024-01-01 Feng Liang , Bichen Wu , Jialiang Wang , Licheng Yu , Kunpeng Li , Yinan Zhao , Ishan Misra , Jia-Bin Huang , Peizhao Zhang , Peter Vajda , Diana Marculescu

This paper presents a new method to synthesize an image from arbitrary views and times given a collection of images of a dynamic scene. A key challenge for the novel view synthesis arises from dynamic scene reconstruction where epipolar…

Computer Vision and Pattern Recognition · Computer Science 2020-04-06 Jae Shin Yoon , Kihwan Kim , Orazio Gallo , Hyun Soo Park , Jan Kautz

In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiaolong Li , Jiawei Mo , Ying Wang , Chethan Parameshwara , Xiaohan Fei , Ashwin Swaminathan , CJ Taylor , Zhuowen Tu , Paolo Favaro , Stefano Soatto

Current one-pass 3D scene synthesis methods often suffer from spatial hallucinations, such as collisions, due to a lack of deliberative reasoning. To bridge this gap, we introduce SceneReVis, a vision-grounded self-reflection framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Yang Zhao , Shizhao Sun , Meisheng Zhang , Yingdong Shi , Xubo Yang , Jiang Bian

We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only $1$ minute.The key component is a dual-mode multi-view latent diffusion model. Given the noisy multi-view latents, the 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Xinyang Li , Zhangyu Lai , Linning Xu , Jianfei Guo , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

DreamFusion has recently demonstrated the utility of a pre-trained text-to-image diffusion model to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesis results. However, the method has two inherent limitations:…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Chen-Hsuan Lin , Jun Gao , Luming Tang , Towaki Takikawa , Xiaohui Zeng , Xun Huang , Karsten Kreis , Sanja Fidler , Ming-Yu Liu , Tsung-Yi Lin

Prompt-driven scene synthesis allows users to generate complete 3D environments from textual descriptions. Current text-to-scene methods often struggle with complex geometries and object transformations, and tend to show weak adherence to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Frédéric Berdoz , Luca A. Lanzendörfer , Nick Tuninga , Roger Wattenhofer

Generating multiview images from a single view facilitates the rapid generation of a 3D mesh conditioned on a single image. Recent methods that introduce 3D global representation into diffusion models have shown the potential to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Zehuan Huang , Hao Wen , Junting Dong , Yaohui Wang , Yangguang Li , Xinyuan Chen , Yan-Pei Cao , Ding Liang , Yu Qiao , Bo Dai , Lu Sheng

In spite of the rapidly evolving landscape of text-to-image generation, the synthesis and manipulation of multiple entities while adhering to specific relational constraints pose enduring challenges. This paper introduces an innovative…

Computer Vision and Pattern Recognition · Computer Science 2024-01-22 YuTeng Ye , Jiale Cai , Hang Zhou , Guanwen Li , Youjia Zhang , Zikai Song , Chenxing Gao , Junqing Yu , Wei Yang

Generating human portraits is a hot topic in the image generation area, e.g. mask-to-face generation and text-to-face generation. However, these unimodal generation methods lack controllability in image generation. Controllability can be…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Debin Meng , Christos Tzelepis , Ioannis Patras , Georgios Tzimiropoulos