641 citations · 3k across the 58 of their papers we have counts for
12 papers · 1 filter
A Discriminative Single-Shot Segmentation Network for Visual Object Tracking
Alan Lukežič, Jiří Matas, Matej Kristan
Template-based discriminative trackers are currently the dominant tracking paradigm due to their robustness, but are restricted to bounding box tracking and a limited range of tran…
Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook
Sajid Javed, Martin Danelljan, Fahad Shahbaz Khan +3
Accurate and robust visual object tracking is one of the most challenging and fundamental computer vision problems. It entails estimating the trajectory of the target in an image s…
Point Cloud Color Constancy
Xiaoyan Xing, Yanlin Qian, Sibo Feng +2
In this paper, we present Point Cloud Color Constancy, in short PCCC, an illumination chromaticity estimation algorithm exploiting a point cloud. We leverage the depth information…
Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds
Dengxin Dai, Arun Balajee Vasudevan, Jiri Matas +1
Humans can robustly recognize and localize objects by using visual and/or auditory cues. While machines are able to do the same with visual data already, less work has been done wi…
Lightweight Monocular Depth with a Novel Neural Architecture Search Method
Lam Huynh, Phong Nguyen, Jiri Matas +2
This paper presents a novel neural architecture search method, called LiDNAS, for generating lightweight monocular depth estimation models. Unlike previous neural architecture sear…
Monocular Depth Estimation Primed by Salient Point Detection and Normalized Hessian Loss
Lam Huynh, Matteo Pedone, Phong Nguyen +3
Deep neural networks have recently thrived on single image depth estimation. That being said, current developments on this topic highlight an apparent compromise between accuracy a…
Recall@k Surrogate Loss with Large Batches and Similarity Mixup
Yash Patel, Giorgos Tolias, Jiri Matas
This work focuses on learning deep visual representation models for retrieval by exploring the interplay between a new loss function, the batch size, and a new regularization appro…
The Hitchhiker's Guide to Prior-Shift Adaptation
Tomas Sipka, Milan Sulc, Jiri Matas
In many computer vision classification tasks, class priors at test time often differ from priors on the training set. In the case of such prior shift, classifiers must be adapted c…
VSAC: Efficient and Accurate Estimator for H and F
Maksym Ivashechkin, Daniel Barath, Jiri Matas
We present VSAC, a RANSAC-type robust estimator with a number of novelties. It benefits from the introduction of the concept of independent inliers that improves significantly the…
USACv20: robust essential, fundamental and homography matrix estimation
Maksym Ivashechkin, Daniel Barath, Jiri Matas
We review the most recent RANSAC-like hypothesize-and-verify robust estimators. The best performing ones are combined to create a state-of-the-art version of the Universal Sample C…
Danish Fungi 2020 -- Not Just Another Image Recognition Dataset
Lukáš Picek, Milan Šulc, Jiří Matas +4
We introduce a novel fine-grained dataset and benchmark, the Danish Fungi 2020 (DF20). The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique…
FEDS -- Filtered Edit Distance Surrogate
Yash Patel, Jiri Matas
This paper proposes a procedure to train a scene text recognition model using a robust learned surrogate of edit distance. The proposed method borrows from self-paced learning and…