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Object Detection

821 papers with code ยท Computer Vision

Object detection is the task of detecting instances of objects of a certain class within an image. The state-of-the-art methods can be categorized into two main types: one-stage methods and two stage-methods. One-stage methods prioritize inference speed, and example models include YOLO, SSD and RetinaNet. Two-stage methods prioritize detection accuracy, and example models include Faster R-CNN, Mask R-CNN and Cascade R-CNN.

The most popular benchmark is the MSCOCO dataset. Models are typically evaluated according to a Mean Average Precision metric.

( Image credit: Detectron )

Benchmarks

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Latest papers without code

Dynamic Edge Weights in Graph Neural Networks for 3D Object Detection

17 Sep 2020

In each layer of the GNN, apart from the linear transformation which maps the per node input features to the corresponding higher level features, a per node masked attention by specifying different weights to different nodes in its first ring neighborhood is also performed.

3D OBJECT DETECTION AUTONOMOUS VEHICLES

POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments

17 Sep 2020

Our POMP method uses as input the current pose of an agent (e. g. a robot) and a RGB-D frame.

MOTION PLANNING OBJECT DETECTION

Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

ECCV 2020

Domain adaptation for object detection tries to adapt the detector from labeled datasets to unlabeled ones for better performance.

DOMAIN ADAPTATION OBJECT DETECTION REGION PROPOSAL

Perceiving Traffic from Aerial Images

16 Sep 2020

Drones or UAVs, equipped with different sensors, have been deployed in many places especially for urban traffic monitoring or last-mile delivery.

OBJECT DETECTION

Hybrid-Attention Guided Network with Multiple Resolution Features for Person Re-Identification

16 Sep 2020

Finally, we reconstruct the feature extractor to ensure that our model can obtain more richer and robust features.

OBJECT DETECTION PERSON RE-IDENTIFICATION

Dual Semantic Fusion Network for Video Object Detection

16 Sep 2020

Video object detection is a tough task due to the deteriorated quality of video sequences captured under complex environments.

OPTICAL FLOW ESTIMATION VIDEO OBJECT DETECTION

Knowledge Guided Learning: Towards Open Domain Egocentric Action Recognition with Zero Supervision

16 Sep 2020

Advances in deep learning have enabled the development of models that have exhibited a remarkable tendency to recognize and even localize actions in videos.

ACTION RECOGNITION DOMAIN ADAPTATION OBJECT DETECTION ZERO-SHOT LEARNING

AMRNet: Chips Augmentation in Areial Images Object Detection

15 Sep 2020

It dynamically adjust cropping size to balance cover proportion between objects and chips, which narrows object scale variation in training and improves performance without bells and whistels; In addtion, we introduce mosaic effective sloving object sparity and background similarity problems in areial dataset; To balance catgory, we present mask resampling in chips providing higher quality training sample; Our model achieves state-of-the-art perfomance on two popular aerial images datasets of VisDrone and UAVDT.

OBJECT DETECTION