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.

OD-VIRAT: A Large-Scale Benchmark for Object Detection in Realistic Surveillance Environments

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Jul 16, 2025
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SS-DC: Spatial-Spectral Decoupling and Coupling Across Visible-Infrared Gap for Domain Adaptive Object Detection

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Jul 16, 2025
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InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based IoU Optimization

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Jul 16, 2025
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Vision-based Perception for Autonomous Vehicles in Obstacle Avoidance Scenarios

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Jul 16, 2025
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AutoVDC: Automated Vision Data Cleaning Using Vision-Language Models

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Jul 16, 2025
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Improving Lightweight Weed Detection via Knowledge Distillation

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Jul 16, 2025
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Frequency-Dynamic Attention Modulation for Dense Prediction

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Jul 16, 2025
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YOLOv8-SMOT: An Efficient and Robust Framework for Real-Time Small Object Tracking via Slice-Assisted Training and Adaptive Association

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Jul 16, 2025
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A Multi-Level Similarity Approach for Single-View Object Grasping: Matching, Planning, and Fine-Tuning

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Jul 16, 2025
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Tree-SLAM: semantic object SLAM for efficient mapping of individual trees in orchards

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Jul 16, 2025
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