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Deep metric learning (DML) is a popular approach for images retrieval, solving verification (same or not) problems and addressing open set classification. Arguably, the most common DML approach is with triplet loss, despite significant…

Machine Learning · Computer Science 2019-12-02 Istvan Fehervari , Avinash Ravichandran , Srikar Appalaraju

In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context. Successful mapping algorithms have been proposed in the last decade building the map leveraging on data from a single…

Computer Vision and Pattern Recognition · Computer Science 2017-08-21 Andrea Romanoni , Daniele Fiorenti , Matteo Matteucci

A depth map can be represented by a set of learned bases and can be efficiently solved in a closed form solution. However, one issue with this method is that it may create artifacts when colour boundaries are inconsistent with depth…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Yiran Zhong , Yuchao Dai , Hongdong Li

Safe motion planning in robotics requires planning into space which has been verified to be free of obstacles. However, obtaining such environment representations using lidars is challenging by virtue of the sparsity of their depth…

We introduce an approach for the real-time (2Hz) creation of a dense map and alignment of a moving robotic agent within that map by rendering using a Graphics Processing Unit (GPU). This is done by recasting the scan alignment part of the…

Computer Vision and Pattern Recognition · Computer Science 2017-02-23 Julian Ryde , Xuchu , Ding

Airborne laser scanning and photogrammetry are two main techniques to obtain 3D data representing the object surface. Due to the high cost of laser scanning, we want to explore the potential of using point clouds derived by dense image…

Computer Vision and Pattern Recognition · Computer Science 2018-07-26 Zhenchao Zhang , Markus Gerke , George Vosselman , Michael Ying Yang

It is common to address the curse of dimensionality in Markov decision processes (MDPs) by exploiting low-rank representations. This motivates much of the recent theoretical study on linear MDPs. However, most approaches require a given…

Machine Learning · Computer Science 2022-12-09 Tianjun Zhang , Tongzheng Ren , Mengjiao Yang , Joseph E. Gonzalez , Dale Schuurmans , Bo Dai

A pre-trained unconditional diffusion model, combined with posterior sampling or maximum a posteriori (MAP) estimation techniques, can solve arbitrary inverse problems without task-specific training or fine-tuning. However, existing…

Machine Learning · Computer Science 2026-02-09 Sai Bharath Chandra Gutha , Ricardo Vinuesa , Hossein Azizpour

Many man-made objects are characterised by a shape that is symmetric along one or more planar directions. Estimating the location and orientation of such symmetry planes can aid many tasks such as estimating the overall orientation of an…

Computer Vision and Pattern Recognition · Computer Science 2021-07-01 Mihaela Cătălina Stoian , Tommaso Cavallari

This report covers our reproduction effort of the paper 'Differentiable Spatial Planning using Transformers' by Chaplot et al. . In this paper, the problem of spatial path planning in a differentiable way is considered. They show that their…

Robotics · Computer Science 2022-08-23 Rohit Ranjan , Himadri Bhakta , Animesh Jha , Parv Maheshwari , Debashish Chakravarty

Ultrasound reflection tomography is widely used to image large complex specimens that are only accessible from a single side, such as well systems and nuclear power plant containment walls. Typical methods for inverting the measurement rely…

Image and Video Processing · Electrical Eng. & Systems 2018-10-01 Hani Almansouri , S. V. Venkatakrishnan , Gregery T. Buzzard , Charles A. Bouman , Hector Santos-Villalobos

Stereo matching plays a crucial role in 3D perception and scenario understanding. Despite the proliferation of promising methods, addressing texture-less and texture-repetitive conditions remains challenging due to the insufficient…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Tong Zhao , Mingyu Ding , Wei Zhan , Masayoshi Tomizuka , Yintao Wei

Accurate depth information is essential for many computer vision applications. Yet, no available dataset recording method allows for fully dense accurate depth estimation in a large scale dynamic environment. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Simon de Moreau , Mathias Corsia , Hassan Bouchiba , Yasser Almehio , Andrei Bursuc , Hafid El-Idrissi , Fabien Moutarde

The estimation of multi-parametric quantitative maps from Magnetic Resonance Fingerprinting (MRF) compressed sampled acquisitions, albeit successful, remains a challenge due to the high underspampling rate and artifacts naturally occuring…

Image and Video Processing · Electrical Eng. & Systems 2024-07-30 Perla Mayo , Matteo Cencini , Ketan Fatania , Carolin M. Pirkl , Marion I. Menzel , Bjoern H. Menze , Michela Tosetti , Mohammad Golbabaee

Lacking realistic ground truth data, image denoising techniques are traditionally evaluated on images corrupted by synthesized i.i.d. Gaussian noise. We aim to obviate this unrealistic setting by developing a methodology for benchmarking…

Computer Vision and Pattern Recognition · Computer Science 2017-07-06 Tobias Plötz , Stefan Roth

Recent feed-forward geometry foundation models have demonstrated impressive generalization by recovering depth and poses in a single forward pass. However, these models are typically constrained by a global coordinate frame assumption. This…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Congrong Xu , Huachen Gao , Xingyu Chen , Yuliang Xiu , Jun Gao , Anpei Chen

In Computer Vision, finding simple features is performed using classifiers called interest point (IP) detectors, which are often utilised to track features as the scene changes. For 2D based classifiers it has been intuitive to measure…

Computer Vision and Pattern Recognition · Computer Science 2019-03-06 Simon R Lang , Martin H Luerssen , David M Powers

Assessing whether a sample survey credibly represents the population is a critical question for ensuring the validity of downstream research. Generally, this problem reduces to estimating the distance between two high-dimensional…

Machine Learning · Computer Science 2025-08-29 Debabrota Basu , Sourav Chakraborty , Debarshi Chanda , Buddha Dev Das , Arijit Ghosh , Arnab Ray

This paper is concerned with polarimetric dense map reconstruction based on a polarization camera with the help of relative depth information as a prior. In general, polarization imaging is able to reveal information about surface normal…

Computer Vision and Pattern Recognition · Computer Science 2021-02-11 Moein Shakeri , Shing Yan Loo , Hong Zhang

In this paper, we introduce the new task of reconstructing 3D human pose from a single image in which we can see the person and the person's image through a mirror. Compared to general scenarios of 3D pose estimation from a single view, the…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Qi Fang , Qing Shuai , Junting Dong , Hujun Bao , Xiaowei Zhou
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