Object Detection


Object detection is a computer vision task in which the goal is to detect and locate objects of interest in an image or video. The task involves identifying the position and boundaries of objects in an image, and classifying the objects into different categories. It forms a crucial part of vision recognition, alongside image classification and retrieval.

SCOOTER: A Human Evaluation Framework for Unrestricted Adversarial Examples

Add code
Jul 10, 2025
Viaarxiv icon

DS@GT at CheckThat! 2025: Detecting Subjectivity via Transfer-Learning and Corrective Data Augmentation

Add code
Jul 08, 2025
Viaarxiv icon

PLOT: Pseudo-Labeling via Video Object Tracking for Scalable Monocular 3D Object Detection

Add code
Jul 03, 2025
Viaarxiv icon

Partial Weakly-Supervised Oriented Object Detection

Add code
Jul 03, 2025
Viaarxiv icon

Automatic Labelling for Low-Light Pedestrian Detection

Add code
Jul 03, 2025
Viaarxiv icon

Weakly-supervised Contrastive Learning with Quantity Prompts for Moving Infrared Small Target Detection

Add code
Jul 03, 2025
Viaarxiv icon

Red grape detection with accelerated artificial neural networks in the FPGA's programmable logic

Add code
Jul 03, 2025
Viaarxiv icon

Two-Steps Neural Networks for an Automated Cerebrovascular Landmark Detection

Add code
Jul 03, 2025
Viaarxiv icon

Perception Activator: An intuitive and portable framework for brain cognitive exploration

Add code
Jul 03, 2025
Viaarxiv icon

A Late Collaborative Perception Framework for 3D Multi-Object and Multi-Source Association and Fusion

Add code
Jul 03, 2025
Viaarxiv icon