Search Results for author:
Found 10 papers, 3 papers with code
Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers
Vision transformers have excelled in various computer vision tasks but mostly rely on rigid input sampling using a fixed-size grid of patches.
Active Visual Exploration Based on Attention-Map Entropy
Active visual exploration addresses the issue of limited sensor capabilities in real-world scenarios, where successive observations are actively chosen based on the environment.
Graph-Based Multi-Camera Soccer Player Tracker
The paper presents a multi-camera tracking method intended for tracking soccer players in long shot video recordings from multiple calibrated cameras installed around the playing field.
Sports Camera Pose Refinement Using an Evolution Strategy
This paper presents a robust end-to-end method for sports cameras extrinsic parameters optimization using a novel evolution strategy.
SuperNCN: Neighbourhood consensus network for robust outdoor scenes matching
In this paper, we present a framework for computing dense keypoint correspondences between images under strong scene appearance changes.
FootAndBall: Integrated player and ball detector
The paper describes a deep neural network-based detector dedicated for ball and players detection in high resolution, long shot, video recordings of soccer matches.
DeepBall: Deep Neural-Network Ball Detector
The paper describes a deep network based object detector specialized for ball detection in long shot videos.
Ranked #7 on
Sports Ball Detection and Tracking
on Volleyball
SConE: Siamese Constellation Embedding Descriptor for Image Matching
Numerous computer vision applications rely on local feature descriptors, such as SIFT, SURF or FREAK, for image matching.
Robust Method of Vote Aggregation and Proposition Verification for Invariant Local Features
This paper presents a method for analysis of the vote space created from the local features extraction process in a multi-detection system.
A framework for robust object multi-detection with a vote aggregation and a cascade filtering
This paper presents a framework designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves.
