Add to ORKGWe develop an all-in-one computer vision toolbox named EasyCV to facilitate the use of various SOTA computer vision methods. Recently, we add YOLOX-PAI, an improved version of YOLOX, into EasyCV. We conduct ablation studies to investigate the influence of some detection methods on YOLOX. We also provide an easy use for PAI-Blade which is used to accelerate the inference process based on BladeDISC and TensorRT. Finally, we receive 42.8 mAP on COCO dateset within 1.0 ms on a single NVIDIA V100 GPU, which is a bit faster than YOLOv6. A simple but efficient predictor api is also designed in EasyCV to conduct end2end object detection. Codes and models are now available at: https://github.com/alibaba/EasyCV.Comment: 5 pages, 5 figure
Object detection is a technique that allows detecting and locating objects in videos and images. Obj...
Although the YOLOv2 method is extremely fast on object detection, its detection accuracy is restrict...
Object Detection is one of the most resource-intensive tasks for Convolutional Neural Networks (CNN)...
For years, the YOLO series has been the de facto industry-level standard for efficient object detect...
YOLO has become a central real-time object detection system for robotics, driverless cars, and video...
AI has led to significant advancements in computer vision and image processing tasks, enabling a wid...
In this report, we present PP-YOLOE, an industrial state-of-the-art object detector with high perfor...
Object detection is considered one of the most challenging problemsin this field of computer vision,...
Computer Vision is a field of study that helps to develop techniques to identify images and displays...
Real-time object detection on Unmanned Aerial Vehicles (UAVs) is a challenging issue due to the limi...
Abstract Computer Vision (CV) is a computer science field where the focus is to study how can comput...
In this study, we examine the associations between channel features and convolutional kernels during...
The state-of-the-art YOLOv4 object detector has already demonstrated its effective inference (65 fr...
The "You only look once v4"(YOLOv4) is one type of object detection methods in deep learning. YOLOv4...
International audienceAs much as an object detector should be accurate, it should be light and fast ...
Object detection is a technique that allows detecting and locating objects in videos and images. Obj...
Although the YOLOv2 method is extremely fast on object detection, its detection accuracy is restrict...
Object Detection is one of the most resource-intensive tasks for Convolutional Neural Networks (CNN)...
For years, the YOLO series has been the de facto industry-level standard for efficient object detect...
YOLO has become a central real-time object detection system for robotics, driverless cars, and video...
AI has led to significant advancements in computer vision and image processing tasks, enabling a wid...
In this report, we present PP-YOLOE, an industrial state-of-the-art object detector with high perfor...
Object detection is considered one of the most challenging problemsin this field of computer vision,...
Computer Vision is a field of study that helps to develop techniques to identify images and displays...
Real-time object detection on Unmanned Aerial Vehicles (UAVs) is a challenging issue due to the limi...
Abstract Computer Vision (CV) is a computer science field where the focus is to study how can comput...
In this study, we examine the associations between channel features and convolutional kernels during...
The state-of-the-art YOLOv4 object detector has already demonstrated its effective inference (65 fr...
The "You only look once v4"(YOLOv4) is one type of object detection methods in deep learning. YOLOv4...
International audienceAs much as an object detector should be accurate, it should be light and fast ...
Object detection is a technique that allows detecting and locating objects in videos and images. Obj...
Although the YOLOv2 method is extremely fast on object detection, its detection accuracy is restrict...
Object Detection is one of the most resource-intensive tasks for Convolutional Neural Networks (CNN)...
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