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.

Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection

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Jun 06, 2025
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CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing

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Jun 09, 2025
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Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods

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Jun 09, 2025
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Synthetic Dataset Generation for Autonomous Mobile Robots Using 3D Gaussian Splatting for Vision Training

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Jun 05, 2025
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VoxDet: Rethinking 3D Semantic Occupancy Prediction as Dense Object Detection

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Jun 05, 2025
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FALO: Fast and Accurate LiDAR 3D Object Detection on Resource-Constrained Devices

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Jun 04, 2025
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Gen-n-Val: Agentic Image Data Generation and Validation

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Jun 05, 2025
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Hallucinate, Ground, Repeat: A Framework for Generalized Visual Relationship Detection

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Jun 06, 2025
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PhysLab: A Benchmark Dataset for Multi-Granularity Visual Parsing of Physics Experiments

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Jun 07, 2025
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Perception Characteristics Distance: Measuring Stability and Robustness of Perception System in Dynamic Conditions under a Certain Decision Rule

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Jun 10, 2025
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