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 …
Object detection using deep learning, CNNs and vision transformers: A review
Detecting objects remains one of computer vision and image understanding applications'
most fundamental and challenging aspects. Significant advances in object detection have …
most fundamental and challenging aspects. Significant advances in object detection have …
Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection
Object detection has been dominated by anchor-based detectors for several years.
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …
Deep high-resolution representation learning for visual recognition
High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …
High-resolution representations for labeling pixels and regions
High-resolution representation learning plays an essential role in many vision problems, eg,
pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite …
pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite …
M3d-rpn: Monocular 3d region proposal network for object detection
Understanding the world in 3D is a critical component of urban autonomous driving.
Generally, the combination of expensive LiDAR sensors and stereo RGB imaging has been …
Generally, the combination of expensive LiDAR sensors and stereo RGB imaging has been …
A comprehensive and systematic look up into deep learning based object detection techniques: A review
Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …
recognition task in computer vision and it has received great attention over the past few …
Sequence level semantics aggregation for video object detection
Video objection detection (VID) has been a rising research direction in recent years. A
central issue of VID is the appearance degradation of video frames caused by fast motion …
central issue of VID is the appearance degradation of video frames caused by fast motion …
CE-FPN: enhancing channel information for object detection
Feature pyramid network (FPN) has been an efficient framework to extract multi-scale
features in object detection. However, current FPN-based methods mostly suffer from the …
features in object detection. However, current FPN-based methods mostly suffer from the …
Mlcvnet: Multi-level context votenet for 3d object detection
In this paper, we address the 3D object detection task by capturing multi-level contextual
information with the self-attention mechanism and multi-scale feature fusion. Most existing …
information with the self-attention mechanism and multi-scale feature fusion. Most existing …