New generation deep learning for video object detection: A survey
Video object detection, a basic task in the computer vision field, is rapidly evolving and
widely used. In recent years, deep learning methods have rapidly become widespread in the …
widely used. In recent years, deep learning methods have rapidly become widespread in the …
A review of video object detection: Datasets, metrics and methods
Although there are well established object detection methods based on static images, their
application to video data on a frame by frame basis faces two shortcomings:(i) lack of …
application to video data on a frame by frame basis faces two shortcomings:(i) lack of …
Classification of skin disease using deep learning neural networks with MobileNet V2 and LSTM
Deep learning models are efficient in learning the features that assist in understanding
complex patterns precisely. This study proposed a computerized process of classifying skin …
complex patterns precisely. This study proposed a computerized process of classifying skin …
Bevdet4d: Exploit temporal cues in multi-camera 3d object detection
J Huang, G Huang - arxiv preprint arxiv:2203.17054, 2022 - arxiv.org
Single frame data contains finite information which limits the performance of the existing
vision-based multi-camera 3D object detection paradigms. For fundamentally pushing the …
vision-based multi-camera 3D object detection paradigms. For fundamentally pushing the …
Deep learning for unmanned aerial vehicle-based object detection and tracking: A survey
Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …
recently become a hotspot across the fields of computer vision (CV) and remote sensing …
TransVOD: end-to-end video object detection with spatial-temporal transformers
Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the
need for many hand-designed components in object detection while demonstrating good …
need for many hand-designed components in object detection while demonstrating good …
RegNet: Self-regulated network for image classification
The ResNet and its variants have achieved remarkable successes in various computer
vision tasks. Despite its success in making gradient flow through building blocks, the …
vision tasks. Despite its success in making gradient flow through building blocks, the …
Flexible high-resolution object detection on edge devices with tunable latency
Object detection is a fundamental building block of video analytics applications. While
Neural Networks (NNs)-based object detection models have shown excellent accuracy on …
Neural Networks (NNs)-based object detection models have shown excellent accuracy on …
Tracking pedestrian heads in dense crowd
R Sundararaman… - Proceedings of the …, 2021 - openaccess.thecvf.com
Tracking humans in crowded video sequences is an important constituent of visual scene
understanding. Increasing crowd density challenges visibility of humans, limiting the …
understanding. Increasing crowd density challenges visibility of humans, limiting the …
Interventional video relation detection
Video Visual Relation Detection (VidVRD) aims to semantically describe the dynamic
interactions across visual concepts localized in a video in the form of subject, predicate …
interactions across visual concepts localized in a video in the form of subject, predicate …