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检索条件"主题词=3D Representation Learning"
7 条 记 录,以下是1-10 订阅
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Towards Large-scale 3d representation learning with Multi-dataset Point Prompt Training
Towards Large-scale 3D Representation Learning with Multi-da...
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IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Wu, Xiaoyang Tian, Zhuotao Wen, Xin Peng, Bohao Liu, Xihui Yu, Kaicheng Zhao, Hengshuang Univ Hong Kong Hong Kong Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China Westlake Univ Hangzhou Peoples R China Alibaba Grp Hangzhou Peoples R China
The rapid advancement of deep learning models is often attributed to their ability to leverage massive training data. In contrast, such privilege has not yet fully benefited 3d deep learning, mainly due to the limited... 详细信息
来源: 评论
JM3d & JM3d-LLM: Elevating 3d representation With Joint Multi-Modal Cues
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IEEE TRANSACTIONS ON PATTERN ANALYSIS ANd MACHINE INTELLIGENCE 2025年 第4期47卷 2475-2492页
作者: Ji, Jiayi Wang, Haowei Wu, Changli Ma, Yiwei Sun, Xiaoshuai Ji, Rongrong Xiamen Univ Key Lab Multimedia Trusted Percept & Efficient Com Minist Educ China Xiamen 361005 Peoples R China Natl Univ Singapore Singapore 119077 Singapore Tencent Youtu Lab Shanghai 200000 Peoples R China
The rising importance of 3d representation learning, pivotal in computer vision, autonomous driving, and robotics, is evident. However, a prevailing trend, which straightforwardly resorted to transferring 2d alignment... 详细信息
来源: 评论
MULTIVIEW LONG-SHORT SPATIAL CONTRASTIVE learning FOR 3d MEdICAL IMAGE ANALYSIS  47
MULTIVIEW LONG-SHORT SPATIAL CONTRASTIVE LEARNING FOR 3D MED...
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47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Cao, Gongpeng Wang, Yiping Zhang, Manli Zhang, Jing Kang, Guixia Xu, Xin Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Wireless Commun Beijing 100876 Peoples R China Gen Hosp PLA Dept Neurosurg Beijing 100853 Peoples R China
The success of supervised deep learning heavily depends on large labeled datasets whose construction is often challenging in medical image analysis. Contrastive learning, a variant of self-supervised learning, is a po... 详细信息
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Balanced Class-Incremental 3d Object Classification and Retrieval
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IEEE TRANSACTIONS ON KNOWLEdGE ANd dATA ENGINEERING 2024年 第1期36卷 35-48页
作者: Liu, An-An Lu, Haochun Zhou, Heyu Li, Tianbao Kankanhalli, Mohan Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Hefei Comprehens Natl Sci Ctr Inst Artificial Intelligence Hefei 230088 Anhui Peoples R China Natl Univ Singapore Sch Comp Singapore 117543 Singapore
Most existing 3d object classification and retrieval algorithms rely on one-off supervised learning on closed 3d object sets and tend to provide rigid convolutional neural networks with little scalability. Such limita... 详细信息
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Lang3dSG: Language-based contrastive pre-training for 3d Scene Graph prediction  11
Lang3DSG: Language-based contrastive pre-training for 3D Sce...
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International Conference in 3d Vision (3dV)
作者: Koch, Sebastian Hermosilla, Pedro Vaskevicius, Narunas Colosi, Mirco Ropinski, Timo Bosch Ctr Artificial Intelligence Renningen Peoples R China Robert Bosch Corp Res Renningen Germany Univ Ulm Ulm Germany TU Vienna Vienna Austria
3d scene graphs are an emerging 3d scene representation, that models both the objects present in the scene as well as their relationships. However, learning 3d scene graphs is a challenging task because it requires no... 详细信息
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Language-Grounded Indoor 3d Semantic Segmentation in the Wild  1
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17th European Conference on Computer Vision (ECCV)
作者: Rozenberszki, david Litany, Or dai, Angela Tech Univ Munich Munich Germany NVIDIA Santa Clara CA USA
Recent advances in 3d semantic segmentation with deep neural networks have shown remarkable success, with rapid performance increase on available datasets. However, current 3d semantic segmentation benchmarks contain ... 详细信息
来源: 评论
Atom-ProteinQA: Atom-level protein model quality assessment through fine-grained joint learning
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COMPUTER METHOdS ANd PROGRAMS IN BIOMEdICINE 2024年 249卷 108078-108078页
作者: Han, Yatong Lu, Yingfeng Yan, Xu Cui, Hannah Cheng, Shenghui Zheng, Jiayou Zhou, Yuzhe Wang, Sheng Li, Zhen Chinese Univ Hong Kong Shenzhen Future Network Intelligence Inst Shenzhen 518172 Peoples R China Chinese Univ Hong Kong Shenzhen Sch Sci & Engn Shenzhen 518172 Peoples R China Westlake Univ Hangzhou 310024 Peoples R China Shanghai Zelixir Biotech Co Ltd Shanghai 200030 Peoples R China
Motivation: Protein model quality assessment (ProteinQA) is a fundamental task that is essential for biologically relevant applications, i.e., protein structure refinement, protein design, etc. Previous works aimed to... 详细信息
来源: 评论