2681 papers with code • 1 benchmarks • 2 datasets

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Use these libraries to find object-detection models and implementations
49 papers
16 papers
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Most implemented papers

Res2Net: A New Multi-scale Backbone Architecture

rwightman/pytorch-image-models 2 Apr 2019

We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e. g., CIFAR-100 and ImageNet.

MnasNet: Platform-Aware Neural Architecture Search for Mobile

tensorflow/tpu CVPR 2019

In this paper, we propose an automated mobile neural architecture search (MNAS) approach, which explicitly incorporate model latency into the main objective so that the search can identify a model that achieves a good trade-off between accuracy and latency.

MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

apple/ml-cvnets ICLR 2022

Light-weight convolutional neural networks (CNNs) are the de-facto for mobile vision tasks.

HarDNet: A Low Memory Traffic Network

PingoLH/Pytorch-HarDNet ICCV 2019

We propose a Harmonic Densely Connected Network to achieve high efficiency in terms of both low MACs and memory traffic.

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

Zzh-tju/DIoU 19 Nov 2019

By incorporating DIoU and CIoU losses into state-of-the-art object detection algorithms, e. g., YOLO v3, SSD and Faster RCNN, we achieve notable performance gains in terms of not only IoU metric but also GIoU metric.

Group Normalization

ppwwyyxx/GroupNorm-reproduce ECCV 2018

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

SOLOv2: Dynamic and Fast Instance Segmentation

WXinlong/SOLO NeurIPS 2020

Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location.

Random Erasing Data Augmentation

zhunzhong07/Random-Erasing 16 Aug 2017

In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN).

Visual Attention Network

Visual-Attention-Network/VAN-Classification 20 Feb 2022

In this paper, we propose a novel linear attention named large kernel attention (LKA) to enable self-adaptive and long-range correlations in self-attention while avoiding its shortcomings.

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

deeplab/deeplab-public 22 Dec 2014

This is due to the very invariance properties that make DCNNs good for high level tasks.