Robust Object Detector with Denoising Paradigm of Consistency Model
Object detection can be effectively formulated as a denoising diffusion process, where the Consistency Model offers a more efficient one-step denoising mechanism compared to the conventional iterative denoising of Diffusion Models.
InstaGen: Generating Synthetic Datasets for Enhancing Object Detection Performance
InstaGen, a novel paradigm to enhance object detection capabilities by training on synthetic datasets generated from diffusion models, demonstrates superior performance over existing state-of-the-art methods in open-vocabulary and data-sparse scenarios.
Leveraging Transfer Learning for Efficient Few-Shot Object Detection
Combining few-shot learning and object detection techniques to rapidly adapt to novel objects with limited annotated samples.
Real-Time End-to-End Object Detector RT-DETR Outperforms Advanced YOLO Models
RT-DETR, the first real-time end-to-end object detector, outperforms previously advanced YOLO detectors in both speed and accuracy, while eliminating the negative impact of NMS post-processing.
Enhancing Object Detector Performance through Task-Integrated Knowledge Distillation
The core message of this paper is to propose a novel knowledge distillation method that simultaneously considers the classification and regression tasks of object detectors, enabling accurate assessment of the student model's learning condition and enhancing the effectiveness of knowledge distillation.
RadarDistill: Enhancing Radar-based Object Detection with LiDAR Knowledge Distillation
RadarDistill improves radar-based object detection by distilling LiDAR knowledge, achieving state-of-the-art performance.
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection
Introducing BAM, a novel method for real-time Out-of-Distribution (OoD) detection in object detection without the need for architectural changes.
Attention-based Class-Conditioned Alignment for Multi-Source Domain Adaptive Object Detection
Efficiently aligning class instances across domains improves object detection performance.
Knowledge Distillation in YOLOX-ViT for Side-Scan Sonar Object Detection
Efficiently reducing model size while maintaining high detection accuracy through knowledge distillation in YOLOX-ViT for side-scan sonar object detection.
Robust 3D Object Detection from LiDAR-Radar Point Clouds via Cross-Modal Feature Augmentation
The author presents a novel framework for robust 3D object detection from LiDAR and radar point clouds using cross-modal hallucination, achieving superior performance in both modalities.
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