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.

One Supervisor, Many Modalities: Adaptive Tool Orchestration for Autonomous Queries

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Mar 12, 2026
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EReCu: Pseudo-label Evolution Fusion and Refinement with Multi-Cue Learning for Unsupervised Camouflage Detection

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Mar 12, 2026
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Multi-turn Physics-informed Vision-language Model for Physics-grounded Anomaly Detection

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Mar 16, 2026
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DRIFT: Dual-Representation Inter-Fusion Transformer for Automated Driving Perception with 4D Radar Point Clouds

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Mar 12, 2026
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Continual Few-shot Adaptation for Synthetic Fingerprint Detection

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Mar 15, 2026
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X-GS: An Extensible Open Framework for Perceiving and Thinking via 3D Gaussian Splatting

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Mar 12, 2026
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MG-Grasp: Metric-Scale Geometric 6-DoF Grasping Framework with Sparse RGB Observations

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Mar 17, 2026
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Block-QAOA-Aware Detection with Parameter Transfer for Large-Scale MIMO

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Mar 17, 2026
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Addressing Data Scarcity in 3D Trauma Detection through Self-Supervised and Semi-Supervised Learning with Vertex Relative Position Encoding

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Mar 12, 2026
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Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection

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Mar 16, 2026
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