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Recent advances in foundational Video Diffusion Models (VDMs) have yielded significant progress. Yet, despite the remarkable visual quality of generated videos, reconstructing consistent 3D scenes from these outputs remains challenging, due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yisu Zhang , Chenjie Cao , Tengfei Wang , Xuhui Zuo , Junta Wu , Jianke Zhu , Chunchao Guo

Visual editing with diffusion models has made significant progress but often struggles with complex scenarios that textual guidance alone could not adequately describe, highlighting the need for additional non-text editing prompts. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Hyeonyu Kim , Seokhoon Jeong , Seonghee Han , Chanhyuk Choi , Taehwan Kim

Computer vision techniques play a central role in the perception stack of autonomous vehicles. Such methods are employed to perceive the vehicle surroundings given sensor data. 3D LiDAR sensors are commonly used to collect sparse 3D point…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Lucas Nunes , Rodrigo Marcuzzi , Benedikt Mersch , Jens Behley , Cyrill Stachniss

3D Gaussian Splatting (3DGS) has recently transformed the fields of novel view synthesis and 3D reconstruction due to its ability to accurately model complex 3D scenes and its unprecedented rendering performance. However, a significant…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Alessio Mazzucchelli , Ivan Ojeda-Martin , Fernando Rivas-Manzaneque , Elena Garces , Adrian Penate-Sanchez , Francesc Moreno-Noguer

Precise geometric control in image generation is essential for engineering \& product design and creative industries to control 3D object features accurately in image space. Traditional 3D editing approaches are time-consuming and demand…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Phillip Mueller , Talip Uenlue , Sebastian Schmidt , Marcel Kollovieh , Jiajie Fan , Stephan Guennemann , Lars Mikelsons

Diffusion models have revolutionized text-driven video editing. However, applying these methods to real-world editing encounters two significant challenges: (1) the rapid increase in GPU memory demand as the number of frames grows, and (2)…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Shuzhou Yang , Chong Mou , Jiwen Yu , Yuhan Wang , Xiandong Meng , Jian Zhang

3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

Taking inspiration from recent developments in visual generative tasks using diffusion models, we propose a method for end-to-end speech-driven video editing using a denoising diffusion model. Given a video of a talking person, and a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Dan Bigioi , Shubhajit Basak , Michał Stypułkowski , Maciej Zięba , Hugh Jordan , Rachel McDonnell , Peter Corcoran

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

Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text-driven methods that often suffer from geometric drift or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Stefan Ainetter , Thomas Deixelberger , Edoardo A. Dominici , Philipp Drescher , Konstantinos Vardis , Markus Steinberger

Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of objects. This work presents DisCoScene: a 3Daware generative…

Computer Vision and Pattern Recognition · Computer Science 2022-12-23 Yinghao Xu , Menglei Chai , Zifan Shi , Sida Peng , Ivan Skorokhodov , Aliaksandr Siarohin , Ceyuan Yang , Yujun Shen , Hsin-Ying Lee , Bolei Zhou , Sergey Tulyakov

3D Gaussian Splatting reconstructs scenes by starting from a sparse Structure-from-Motion initialization and refining under-reconstructed regions. This process is slow, as it requires multiple densification steps where Gaussians are…

Graphics · Computer Science 2026-02-13 Dmytro Kotovenko , Olga Grebenkova , Björn Ommer

In this paper, we propose an efficient, fast, and versatile distillation method to accelerate the generation of pre-trained diffusion models: Flash Diffusion. The method reaches state-of-the-art performances in terms of FID and CLIP-Score…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Clément Chadebec , Onur Tasar , Eyal Benaroche , Benjamin Aubin

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

Novel-view synthesis aims to generate novel views of a scene from multiple input images or videos, and recent advancements like 3D Gaussian splatting (3DGS) have achieved notable success in producing photorealistic renderings with efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xi Liu , Chaoyi Zhou , Siyu Huang

3D Gaussian Splatting (3DGS) has demonstrated remarkable performance in scene synthesis and novel view synthesis tasks. Typically, the initialization of 3D Gaussian primitives relies on point clouds derived from Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Shan Chen , Jiale Zhou , Lei Li

Recent advancements in 3D reconstruction from single images have been driven by the evolution of generative models. Prominent among these are methods based on Score Distillation Sampling (SDS) and the adaptation of diffusion models in the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Zi-Xin Zou , Zhipeng Yu , Yuan-Chen Guo , Yangguang Li , Ding Liang , Yan-Pei Cao , Song-Hai Zhang

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3DGS leverages GPU rasterization pipelines for efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Peihao Wang , Yuehao Wang , Dilin Wang , Sreyas Mohan , Zhiwen Fan , Lemeng Wu , Ruisi Cai , Yu-Ying Yeh , Zhangyang Wang , Qiang Liu , Rakesh Ranjan

Recent advances in 3D Gaussian Splatting (3DGS) deliver striking photorealism, and extending it to large scenes opens new opportunities for semantic reasoning and prediction in applications such as autonomous driving. Today's…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Shengkai Zhang , Yuhe Liu , Jianhua He , Xuedou Xiao , Mozi Chen , Kezhong Liu
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