26 citations · 92 across the 21 of their papers we have counts for
11 papers · 2 filters
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…
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…