ICCV
Collection
Accepted papers for ICCV (IEEE/CVF International Conference on Computer Vision), one dataset per year. • 7 items • Updated
paper_id uint32 0 620 | title stringlengths 10 144 | authors listlengths 1 14 | cvf_url stringlengths 87 127 | pdf_url stringlengths 88 128 | supp_url stringlengths 105 136 ⌀ | arxiv_id stringlengths 10 12 ⌀ | arxiv_id_source stringclasses 3
values | bibtex large_stringlengths 207 546 | abstract large_stringlengths 441 2.03k ⌀ | embedding listlengths 768 768 |
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0 | Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence | [
"Dylan Campbell",
"Lars Petersson",
"Laurent Kneip",
"Hongdong Li"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Campbell_Globally-Optimal_Inlier_Set_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Campbell_Globally-Optimal_Inlier_Set_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Campbell_Globally-Optimal_Inlier_Set_ICCV_2017_supplemental.pdf | 1709.09384v1 | cvf | @InProceedings{Campbell_2017_ICCV,author = {Campbell, Dylan and Petersson, Lars and Kneip, Laurent and Li, Hongdong},title = {Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month =... | Estimating the 6-DoF pose of a camera from a single image relative to a pre-computed 3D point-set is an important task for many computer vision applications. Perspective-n-Point (PnP) solvers are routinely used for camera pose estimation, provided that a good quality set of 2D-3D feature correspondences are known befor... | [
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1 | Robust Pseudo Random Fields for Light-Field Stereo Matching | [
"Chao-Tsung Huang"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Huang_Robust_Pseudo_Random_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Huang_Robust_Pseudo_Random_ICCV_2017_paper.pdf | null | null | null | @InProceedings{Huang_2017_ICCV,author = {Huang, Chao-Tsung},title = {Robust Pseudo Random Fields for Light-Field Stereo Matching},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oct},year = {2017}} | Markov Random Fields are widely used to model light-field stereo matching problems. However, most previous approaches used fixed parameters and did not adapt to light-field statistics. Instead, they explored explicit vision cues to provide local adaptability and thus enhanced depth quality. But such additional assumpti... | [
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2 | A Lightweight Approach for On-The-Fly Reflectance Estimation | [
"Kihwan Kim",
"Jinwei Gu",
"Stephen Tyree",
"Pavlo Molchanov",
"Matthias Niessner",
"Jan Kautz"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Kim_A_Lightweight_Approach_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Kim_A_Lightweight_Approach_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Kim_A_Lightweight_Approach_ICCV_2017_supplemental.pdf | 1705.07162v2 | cvf | @InProceedings{Kim_2017_ICCV,author = {Kim, Kihwan and Gu, Jinwei and Tyree, Stephen and Molchanov, Pavlo and Niessner, Matthias and Kautz, Jan},title = {A Lightweight Approach for On-The-Fly Reflectance Estimation},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oct},y... | Estimating surface reflectance (BRDF) is one key component for complete 3D scene capture, with wide applications in virtual reality, augmented reality, and human computer interaction. Prior work is either limited to controlled environments (e.g., gonioreflectometers, light stages or multi-camera domes), or requires the... | [
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3 | Distributed Very Large Scale Bundle Adjustment by Global Camera Consensus | [
"Runze Zhang",
"Siyu Zhu",
"Tian Fang",
"Long Quan"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Distributed_Very_Large_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_Distributed_Very_Large_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Zhang_Distributed_Very_Large_ICCV_2017_supplemental.pdf | null | null | @InProceedings{Zhang_2017_ICCV,author = {Zhang, Runze and Zhu, Siyu and Fang, Tian and Quan, Long},title = {Distributed Very Large Scale Bundle Adjustment by Global Camera Consensus},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oct},year = {2017}} | The increasing scale of Structure-from-Motion is fundamentally limited by the conventional optimization framework for the all-in-one global bundle adjustment. In this paper, we propose a distributed approach to coping with this global bundle adjustment for very large scale Structure-from-Motion computation. First, we d... | [
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4 | Practical Projective Structure From Motion (P2SfM) | [
"Ludovic Magerand",
"Alessio Del Bue"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Magerand_Practical_Projective_Structure_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Magerand_Practical_Projective_Structure_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Magerand_Practical_Projective_Structure_ICCV_2017_supplemental.zip | null | null | @InProceedings{Magerand_2017_ICCV,author = {Magerand, Ludovic and Del Bue, Alessio},title = {Practical Projective Structure From Motion (P2SfM)},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oct},year = {2017}} | This paper presents a solution to the Projective Structure from Motion (PSfM) problem able to deal efficiently with missing data, outliers and, for the first time, large scale 3D reconstruction scenarios. By embedding the projective depths into the projective parameters of the points and views, we decrease the number o... | [
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5 | Anticipating Daily Intention Using On-Wrist Motion Triggered Sensing | [
"Tz-Ying Wu",
"Ting-An Chien",
"Cheng-Sheng Chan",
"Chan-Wei Hu",
"Min Sun"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Wu_Anticipating_Daily_Intention_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Wu_Anticipating_Daily_Intention_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Wu_Anticipating_Daily_Intention_ICCV_2017_supplemental.pdf | 1710.07477v1 | cvf | @InProceedings{Wu_2017_ICCV,author = {Wu, Tz-Ying and Chien, Ting-An and Chan, Cheng-Sheng and Hu, Chan-Wei and Sun, Min},title = {Anticipating Daily Intention Using On-Wrist Motion Triggered Sensing},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oct},year = {2017}} | Anticipating human intention by observing one's actions has many applications. For instance, picking up a cellphone, then a charger (actions) implies that one wants to charge the cellphone (intention). By anticipating the intention, an intelligent system can guide the user to the closest power outlet. We propose an on-... | [
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6 | Rethinking Reprojection: Closing the Loop for Pose-Aware Shape Reconstruction From a Single Image | [
"Rui Zhu",
"Hamed Kiani Galoogahi",
"Chaoyang Wang",
"Simon Lucey"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Rethinking_Reprojection_Closing_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Zhu_Rethinking_Reprojection_Closing_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Zhu_Rethinking_Reprojection_Closing_ICCV_2017_supplemental.pdf | 1707.04682 | title_judge | @InProceedings{Zhu_2017_ICCV,author = {Zhu, Rui and Kiani Galoogahi, Hamed and Wang, Chaoyang and Lucey, Simon},title = {Rethinking Reprojection: Closing the Loop for Pose-Aware Shape Reconstruction From a Single Image},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oc... | An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image. Hitherto, the problem has been addressed through the application of canonical deep learning methods to regress from the image directly to the 3D shape and pose labels. These approaches, however, are probl... | [
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7 | End-To-End Learning of Geometry and Context for Deep Stereo Regression | [
"Alex Kendall",
"Hayk Martirosyan",
"Saumitro Dasgupta",
"Peter Henry",
"Ryan Kennedy",
"Abraham Bachrach",
"Adam Bry"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Kendall_End-To-End_Learning_of_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Kendall_End-To-End_Learning_of_ICCV_2017_paper.pdf | null | 1703.04309v1 | cvf | @InProceedings{Kendall_2017_ICCV,author = {Kendall, Alex and Martirosyan, Hayk and Dasgupta, Saumitro and Henry, Peter and Kennedy, Ryan and Bachrach, Abraham and Bry, Adam},title = {End-To-End Learning of Geometry and Context for Deep Stereo Regression},booktitle = {Proceedings of the IEEE International Conference on ... | We propose a novel deep learning architecture for regressing disparity from a rectified pair of stereo images. We leverage knowledge of the problem's geometry to form a cost volume using deep feature representations. We learn to incorporate contextual information using 3-D convolutions over this volume. Disparity value... | [
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8 | Using Sparse Elimination for Solving Minimal Problems in Computer Vision | [
"Janne Heikkila"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Heikkila_Using_Sparse_Elimination_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Heikkila_Using_Sparse_Elimination_ICCV_2017_paper.pdf | null | null | null | @InProceedings{Heikkila_2017_ICCV,author = {Heikkila, Janne},title = {Using Sparse Elimination for Solving Minimal Problems in Computer Vision},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Oct},year = {2017}} | Finding a closed form solution to a system of polynomial equations is a common problem in computer vision as well as in many other areas of engineering and science. Groebner basis techniques are often employed to provide the solution, but implementing an efficient Groebner basis solver to a given problem requires stron... | [
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9 | High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference | [
"Xiaoguang Han",
"Zhen Li",
"Haibin Huang",
"Evangelos Kalogerakis",
"Yizhou Yu"
] | https://openaccess.thecvf.com/content_iccv_2017/html/Han_High-Resolution_Shape_Completion_ICCV_2017_paper.html | https://openaccess.thecvf.com/content_ICCV_2017/papers/Han_High-Resolution_Shape_Completion_ICCV_2017_paper.pdf | https://openaccess.thecvf.com/content_ICCV_2017/supplemental/Han_High-Resolution_Shape_Completion_ICCV_2017_supplemental.pdf | 1709.07599v1 | cvf | @InProceedings{Han_2017_ICCV,author = {Han, Xiaoguang and Li, Zhen and Huang, Haibin and Kalogerakis, Evangelos and Yu, Yizhou},title = {High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference},booktitle = {Proceedings of the IEEE International Conference on Compute... | We propose a data-driven method for recovering missing parts of 3D shapes. Our method is based on a new deep learning architecture consisting of two sub-networks: a global structure inference network and a local geometry refinement network. The global structure inference network incorporates a long short-term memorized... | [
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