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In this paper, the problem of automating the pre-grasps generation for novel 3d objects has been discussed. The objects represented as cloud of 3D points are split into parts and organized in a tree structure, where parts are approximated…

Robotics · Computer Science 2019-10-01 IA Sainul , Sankha Deb , AK Deb

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

Recently, 3D content creation from text prompts has demonstrated remarkable progress by utilizing 2D and 3D diffusion models. While 3D diffusion models ensure great multi-view consistency, their ability to generate high-quality and diverse…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Fangfu Liu , Diankun Wu , Yi Wei , Yongming Rao , Yueqi Duan

3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. However, traditional methods often require millions of Gaussians to capture complex…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Anh Thuan Tran , Jana Kosecka

Building an efficient and physically consistent world model from limited observations is a long standing challenge in vision and robotics. Many existing world modeling pipelines are based on implicit generative models, which are hard to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Wenhao Hu , Xuexiang Wen , Xi Li , Gaoang Wang

The goal of structure-based drug discovery is to find small molecules that bind to a given target protein. Deep learning has been used to generate drug-like molecules with certain cheminformatic properties, but has not yet been applied to…

Quantitative Methods · Quantitative Biology 2022-01-27 Matthew Ragoza , Tomohide Masuda , David Ryan Koes

Generating ground-level views and coherent 3D site models from aerial-only imagery is challenging due to extreme viewpoint changes, missing intermediate observations, and large scale variations. Existing methods either refine renderings…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Sirshapan Mitra , Yogesh S. Rawat

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

Latent diffusion models for image generation have crossed a quality threshold which enabled them to achieve mass adoption. Recently, a series of works have made advancements towards replicating this success in the 3D domain, introducing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Anchit Gupta , Wenhan Xiong , Yixin Nie , Ian Jones , Barlas Oğuz

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

3D Gaussian Splatting (3DGS) has made significant strides in novel view synthesis but is limited by the substantial number of Gaussian primitives required, posing challenges for deployment on lightweight devices. Recent methods address this…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Zhengqing Gao , Dongting Hu , Jia-Wang Bian , Huan Fu , Yan Li , Tongliang Liu , Mingming Gong , Kun Zhang

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

In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Jianfeng Xiang , Jiaolong Yang , Binbin Huang , Xin Tong

3DGS employs a large number of Gaussian primitives to fit scenes, resulting in substantial storage and computational overhead. Existing pruning methods rely on manually designed criteria or introduce additional learnable parameters,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Xiaobin Deng , Qiuli Yu , Changyu Diao , Min Li , Duanqing Xu

Traditional 3D garment creation is labor-intensive, involving sketching, modeling, UV mapping, and texturing, which are time-consuming and costly. Recent advances in diffusion-based generative models have enabled new possibilities for 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Boqian Li , Xuan Li , Ying Jiang , Tianyi Xie , Feng Gao , Huamin Wang , Yin Yang , Chenfanfu Jiang

Despite recent advances in leveraging generative prior from pre-trained diffusion models for 3D scene reconstruction, existing methods still face two critical limitations. First, due to the lack of reliable geometric supervision, they…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Junfeng Ni , Yixin Chen , Zhifei Yang , Yu Liu , Ruijie Lu , Song-Chun Zhu , Siyuan Huang

Driven by powerful image diffusion models, recent research has achieved the automatic creation of 3D objects from textual or visual guidance. By performing score distillation sampling (SDS) iteratively across different views, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Zeyu Li , Ruitong Gan , Chuanchen Luo , Yuxi Wang , Jiaheng Liu , Ziwei Zhu Man Zhang , Qing Li , Xucheng Yin , Zhaoxiang Zhang , Junran Peng

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling in-the-wild scenes affected by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chuanyu Fu , Guanying Chen , Yuqi Zhang , Kunbin Yao , Yuan Xiong , Chuan Huang , Shuguang Cui , Yasuyuki Matsushita , Xiaochun Cao

Open-vocabulary 3D scene understanding presents a significant challenge in computer vision, with wide-ranging applications in embodied agents and augmented reality systems. Existing methods adopt neurel rendering methods as 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Jun Guo , Xiaojian Ma , Yue Fan , Huaping Liu , Qing Li
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