Browse > Computer Vision > Object Detection

Object Detection

669 papers with code · 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 )

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Latest papers with code

End-to-End Object Detection with Transformers

26 May 2020facebookresearch/detr

We present a new method that views object detection as a direct set prediction problem.

OBJECT DETECTION PANOPTIC SEGMENTATION

2,153
26 May 2020

Attention-guided Context Feature Pyramid Network for Object Detection

23 May 2020Caojunxu/AC-FPN

For object detection, how to address the contradictory requirement between feature map resolution and receptive field on high-resolution inputs still remains an open question.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

35
23 May 2020

Underwater object detection using Invert Multi-Class Adaboost with deep learning

23 May 2020LongChenCV/SWIPENet

In addition, we propose a novel sample-weighted loss function which can model sample weights for SWIPENet, which uses a novel sample re-weighting algorithm, namely Invert Multi-Class Adaboost (IMA), to reduce the influence of noise on the proposed SWIPENet.

SMALL OBJECT DETECTION

0
23 May 2020

What makes for good views for contrastive learning

20 May 2020HobbitLong/PyContrast

Contrastive learning between multiple views of the data has recently achieved state of the art performance in the field of self-supervised representation learning.

CONTRASTIVE LEARNING DATA AUGMENTATION INSTANCE SEGMENTATION OBJECT DETECTION REPRESENTATION LEARNING SELF-SUPERVISED IMAGE CLASSIFICATION SEMANTIC SEGMENTATION

336
20 May 2020

Dynamic Refinement Network for Oriented and Densely Packed Object Detection

20 May 2020Anymake/DRN_CVPR2020

However, the detection of oriented and densely packed objects remains challenging because of following inherent reasons: (1) receptive fields of neurons are all axis-aligned and of the same shape, whereas objects are usually of diverse shapes and align along various directions; (2) detection models are typically trained with generic knowledge and may not generalize well to handle specific objects at test time; (3) the limited dataset hinders the development on this task.

FEATURE SELECTION OBJECT DETECTION

39
20 May 2020

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

18 May 2020NathanUA/U-2-Net

In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).

IMAGE CLASSIFICATION SALIENT OBJECT DETECTION

805
18 May 2020

IterDet: Iterative Scheme for ObjectDetection in Crowded Environments

12 May 2020saic-vul/iterdet

Deep learning-based detectors usually produce a redundant set of object bounding boxes including many duplicate detections of the same object.

OBJECT DETECTION

62
12 May 2020

Stillleben: Realistic Scene Synthesis for Deep Learning in Robotics

12 May 2020AIS-Bonn/stillleben

Training data is the key ingredient for deep learning approaches, but difficult to obtain for the specialized domains often encountered in robotics.

OBJECT DETECTION POSE ESTIMATION SEMANTIC SEGMENTATION

6
12 May 2020

A Simple Semi-Supervised Learning Framework for Object Detection

10 May 2020google-research/ssl_detection

Semi-supervised learning (SSL) has promising potential for improving the predictive performance of machine learning models using unlabeled data.

DATA AUGMENTATION IMAGE CLASSIFICATION OBJECT DETECTION

53
10 May 2020