Object detection in 20 years: A survey
Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …
vision, has received great attention in recent years. Over the past two decades, we have …
Recent advances in convolutional neural networks
In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …
problems, such as visual recognition, speech recognition and natural language processing …
The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Abstract We present Open Images V4, a dataset of 9.2 M images with unified annotations for
image classification, object detection and visual relationship detection. The images have a …
image classification, object detection and visual relationship detection. The images have a …
Deep learning for generic object detection: A survey
Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …
seeks to locate object instances from a large number of predefined categories in natural …
[PDF][PDF] Training region-based object detectors with online hard example mining
The field of object detection has made significant advances riding on the wave of region-
based ConvNets, but their training procedure still includes many heuristics and …
based ConvNets, but their training procedure still includes many heuristics and …
Imagenet large scale visual recognition challenge
Abstract The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object
category classification and detection on hundreds of object categories and millions of …
category classification and detection on hundreds of object categories and millions of …
Deep learning for visual understanding: A review
Deep learning algorithms are a subset of the machine learning algorithms, which aim at
discovering multiple levels of distributed representations. Recently, numerous deep learning …
discovering multiple levels of distributed representations. Recently, numerous deep learning …
Region-based convolutional networks for accurate object detection and segmentation
Object detection performance, as measured on the canonical PASCAL VOC Challenge
datasets, plateaued in the final years of the competition. The best-performing methods were …
datasets, plateaued in the final years of the competition. The best-performing methods were …
Rich feature hierarchies for accurate object detection and semantic segmentation
Object detection performance, as measured on the canonical PASCAL VOC dataset, has
plateaued in the last few years. The best-performing methods are complex ensemble …
plateaued in the last few years. The best-performing methods are complex ensemble …
Recent advances in deep learning for object detection
Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …
been widely studied in the past decades. Visual object detection aims to find objects of …