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We present a novel method for 6-DoF object tracking and high-quality 3D reconstruction from monocular RGBD video. Existing methods, while achieving impressive results, often struggle with complex objects, particularly those exhibiting…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Takuya Ikeda , Sergey Zakharov , Muhammad Zubair Irshad , Istvan Balazs Opra , Shun Iwase , Dian Chen , Mark Tjersland , Robert Lee , Alexandre Dilly , Rares Ambrus , Koichi Nishiwaki

Implicit surface representations are valued for their compactness and continuity, but they pose significant challenges for editing. Despite recent advancements, existing methods often fail to preserve identity and maintain geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Nail Ibrahimli , Julian F. P. Kooij , Liangliang Nan

Existing 3D-aware facial generation methods face a dilemma in quality versus editability: they either generate editable results in low resolution or high-quality ones with no editing flexibility. In this work, we propose a new approach that…

Computer Vision and Pattern Recognition · Computer Science 2022-06-01 Jingxiang Sun , Xuan Wang , Yichun Shi , Lizhen Wang , Jue Wang , Yebin Liu

Image blending aims to combine multiple images seamlessly. It remains challenging for existing 2D-based methods, especially when input images are misaligned due to differences in 3D camera poses and object shapes. To tackle these issues, we…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Hyunsu Kim , Gayoung Lee , Yunjey Choi , Jin-Hwa Kim , Jun-Yan Zhu

This paper presents a pose-free, feed-forward 3D Gaussian Splatting (3DGS) framework designed to handle unfavorable input views. A common rendering setup for training feed-forward approaches places a 3D object at the world origin and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

Many real-world applications, such as interactive photo retouching, artistic content creation, and product design, require flexible and iterative image editing. However, existing image editing methods primarily focus on achieving the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Zijun Zhou , Yingying Deng , Xiangyu He , Weiming Dong , Fan Tang

Facial attribute editing plays a crucial role in synthesizing realistic faces with specific characteristics while maintaining realistic appearances. Despite advancements, challenges persist in achieving precise, 3D-aware attribute…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Yu-Kai Huang , Yutong Zheng , Yen-Shuo Su , Anudeepsekhar Bolimera , Han Zhang , Fangyi Chen , Marios Savvides

Image representation is a fundamental task in computer vision. Recently, Gaussian Splatting has emerged as an efficient representation framework, and its extension to 2D image representation enables lightweight, yet expressive modeling of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Masaya Takabe , Hiroshi Watanabe , Sujun Hong , Tomohiro Ikai , Zheming Fan , Ryo Ishimoto , Kakeru Sugimoto , Ruri Imichi

Reconstructing high-fidelity animatable human avatars from monocular videos remains challenging due to insufficient geometric information in single-view observations. While recent 3D Gaussian Splatting methods have shown promise, they…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Jinlong Fan , Bingyu Hu , Xingguang Li , Yuxiang Yang , Jing Zhang

Morphable Models (3DMMs) are a type of morphable model that takes 2D images as inputs and recreates the structure and physical appearance of 3D objects, especially human faces and bodies. 3DMM combines identity and expression blendshapes…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Gulraiz Khan , Kenneth Y. Wertheim , Kevin Pimbblet , Waqas Ahmed

We propose a novel framework for fine-grained object recognition that learns to recover object variation in 3D space from a single image, trained on an image collection without using any ground-truth 3D annotation. We accomplish this by…

Computer Vision and Pattern Recognition · Computer Science 2021-08-11 Sunghun Joung , Seungryong Kim , Minsu Kim , Ig-Jae Kim , Kwanghoon Sohn

Depth in the real world is rarely singular. Transmissive materials create layered ambiguities that confound conventional perception systems. Existing models remain passive; conventional approaches typically estimate static depth maps…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Junhong Min , Jimin Kim , Minwook Kim , Cheol-Hui Min , Youngpil Jeon , Minyong Choi

Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details. Neural volumetric representations approach photorealism but are hard to animate and do not…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Yufeng Zheng , Victoria Fernández Abrevaya , Marcel C. Bühler , Xu Chen , Michael J. Black , Otmar Hilliges

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

In this paper, we propose a new operator, called 3D DeFormable Attention (DFA3D), for 2D-to-3D feature lifting, which transforms multi-view 2D image features into a unified 3D space for 3D object detection. Existing feature lifting…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Hongyang Li , Hao Zhang , Zhaoyang Zeng , Shilong Liu , Feng Li , Tianhe Ren , Lei Zhang

Feed-forward 3D Gaussian splatting (3DGS) models have gained significant popularity due to their ability to generate scenes immediately without needing per-scene optimization. Although omnidirectional images are becoming more popular since…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Suyoung Lee , Jaeyoung Chung , Kihoon Kim , Jaeyoo Huh , Gunhee Lee , Minsoo Lee , Kyoung Mu Lee

This work prioritizes building a modular pipeline that utilizes existing models to systematically restore images, rather than creating new restoration models from scratch. Restoration is carried out at an object-specific level, with each…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Tom Richard Vargis , Siavash Ghiasvand

To generalize to novel visual scenes with new viewpoints and new object poses, a visual system needs representations of the shapes of the parts of an object that are invariant to changes in viewpoint or pose. 3D graphics representations…

Computer Vision and Pattern Recognition · Computer Science 2019-05-29 Boyang Deng , Simon Kornblith , Geoffrey Hinton

Gaussian Splatting (GS) enables immersive rendering, but realistic 3D object-scene composition remains challenging. Baked appearance and shadow information in GS radiance fields cause inconsistencies when combining objects and scenes.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Jian Gao , Mengqi Yuan , Yifei Zeng , Chang Zeng , Zhihao Li , Zhenyu Chen , Weichao Qiu , Xiao-Xiao Long , Hao Zhu , Xun Cao , Yao Yao
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