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Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered from novel camera views, existing single image to 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Sarosij Bose , Arindam Dutta , Sayak Nag , Junge Zhang , Jiachen Li , Konstantinos Karydis , Amit K. Roy Chowdhury

3D panorama synthesis is a promising yet challenging task that demands high-quality and diverse visual appearance and geometry of the generated omnidirectional content. Existing methods leverage rich image priors from pre-trained 2D…

Graphics · Computer Science 2025-06-23 Yukun Huang , Yanning Zhou , Jianan Wang , Kaiyi Huang , Xihui Liu

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha

The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved success, a unified 3D diffusion pipeline remains unsettled.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yushi Lan , Fangzhou Hong , Shangchen Zhou , Shuai Yang , Xuyi Meng , Yongwei Chen , Zhaoyang Lyu , Bo Dai , Xingang Pan , Chen Change Loy

Inspired by the remarkable success of Latent Diffusion Models (LDMs) for image synthesis, we study LDM for text-to-video generation, which is a formidable challenge due to the computational and memory constraints during both model training…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Jiaxi Gu , Shicong Wang , Haoyu Zhao , Tianyi Lu , Xing Zhang , Zuxuan Wu , Songcen Xu , Wei Zhang , Yu-Gang Jiang , Hang Xu

We present SyncFix, a framework that enforces cross-view consistency during the diffusion-based refinement of reconstructed scenes. SyncFix formulates refinement as a joint latent bridge matching problem, synchronizing distorted and clean…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Deming Li , Abhay Yadav , Cheng Peng , Rama Chellappa , Anand Bhattad

Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Patrick Esser , Johnathan Chiu , Parmida Atighehchian , Jonathan Granskog , Anastasis Germanidis

The remarkable achievements of both generative models of 2D images and neural field representations for 3D scenes present a compelling opportunity to integrate the strengths of both approaches. In this work, we propose a methodology that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Azmi Haider , Dan Rosenbaum

Panoramic video generation aims to synthesize 360-degree immersive videos, holding significant importance in the fields of VR, world models, and spatial intelligence. Existing works fail to synthesize high-quality panoramic videos due to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zixun Fang , Kai Zhu , Zhiheng Liu , Yu Liu , Wei Zhai , Yang Cao , Zheng-Jun Zha

We introduce Intrinsic Image Fusion, a method that reconstructs high-quality physically based materials from multi-view images. Material reconstruction is highly underconstrained and typically relies on analysis-by-synthesis, which requires…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Peter Kocsis , Lukas Höllein , Matthias Nießner

Following rapid advancements in text and image generation, research has increasingly shifted towards 3D generation. Unlike the well-established pixel-based representation in images, 3D representations remain diverse and fragmented,…

The growing demand for Embodied AI and VR applications has highlighted the need for synthesizing high-quality 3D indoor scenes from sparse inputs. However, existing approaches struggle to infer massive amounts of missing geometry in large…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Dehui Wang , Congsheng Xu , Rong Wei , Yue Shi , Shoufa Chen , Dingxiang Luo , Tianshuo Yang , Xiaokang Yang , Wei Sui , Yusen Qin , Rui Tang , Yao Mu

In recent years, 3D vision has become a crucial field within computer vision, powering a wide range of applications such as autonomous driving, robotics, augmented reality, and medical imaging. This field relies on accurate perception,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Zhen Wang , Dongyuan Li , Yaozu Wu , Tianyu He , Jiang Bian , Renhe Jiang

Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether such priors derived from a generative process are suitable for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zejia Weng , Xitong Yang , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Recent diffusion-based video generation models can synthesize visually plausible videos, yet they often struggle to satisfy physical constraints. A key reason is that most existing approaches remain single-stage: they entangle high-level…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Yibo Zhao , Hengjia Li , Xiaofei He , Boxi Wu

Real-world applications like video gaming and virtual reality often demand the ability to model 3D scenes that users can explore along custom camera trajectories. While significant progress has been made in generating 3D objects from text…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Tianyu Huang , Wangguandong Zheng , Tengfei Wang , Yuhao Liu , Zhenwei Wang , Junta Wu , Jie Jiang , Hui Li , Rynson W. H. Lau , Wangmeng Zuo , Chunchao Guo

Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-view data. Existing methods often address these factors separately, resulting in limited…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Zhengwentai Sun , Keru Zheng , Chenghong Li , Hongjie Liao , Xihe Yang , Heyuan Li , Yihao Zhi , Shuliang Ning , Shuguang Cui , Xiaoguang Han

Multimedia generation approaches occupy a prominent place in artificial intelligence research. Text-to-image models achieved high-quality results over the last few years. However, video synthesis methods recently started to develop. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Vladimir Arkhipkin , Zein Shaheen , Viacheslav Vasilev , Elizaveta Dakhova , Andrey Kuznetsov , Denis Dimitrov