No more strided convolutions or pooling: A new CNN building block for low-resolution images and small objects

R Sunkara, T Luo - Joint European conference on machine learning and …, 2022‏ - Springer
Convolutional neural networks (CNNs) have made resounding success in many computer
vision tasks such as image classification and object detection. However, their performance …

Simple open-vocabulary object detection

M Minderer, A Gritsenko, A Stone, M Neumann… - European conference on …, 2022‏ - Springer
Combining simple architectures with large-scale pre-training has led to massive
improvements in image classification. For object detection, pre-training and scaling …

Actionformer: Localizing moments of actions with transformers

CL Zhang, J Wu, Y Li - European Conference on Computer Vision, 2022‏ - Springer
Self-attention based Transformer models have demonstrated impressive results for image
classification and object detection, and more recently for video understanding. Inspired by …

Edgenext: efficiently amalgamated cnn-transformer architecture for mobile vision applications

M Maaz, A Shaker, H Cholakkal, S Khan… - European conference on …, 2022‏ - Springer
In the pursuit of achieving ever-increasing accuracy, large and complex neural networks are
usually developed. Such models demand high computational resources and therefore …

RFLA: Gaussian receptive field based label assignment for tiny object detection

C Xu, J Wang, W Yang, H Yu, L Yu, GS **a - European conference on …, 2022‏ - Springer
Detecting tiny objects is one of the main obstacles hindering the development of object
detection. The performance of generic object detectors tends to drastically deteriorate on tiny …

A comprehensive survey and deep learning-based approach for human recognition using ear biometric

A Kamboj, R Rani, A Nigam - The Visual Computer, 2022‏ - Springer
Human recognition systems based on biometrics are much in demand due to increasing
concerns of security and privacy. The human ear is unique and useful for recognition. It …

Pillarnet: Real-time and high-performance pillar-based 3d object detection

G Shi, R Li, C Ma - European Conference on Computer Vision, 2022‏ - Springer
Real-time and high-performance 3D object detection is of critical importance for autonomous
driving. Recent top-performing 3D object detectors mainly rely on point-based or 3D voxel …

End-to-end object detection with transformers

N Carion, F Massa, G Synnaeve, N Usunier… - European conference on …, 2020‏ - Springer
We present a new method that views object detection as a direct set prediction problem. Our
approach streamlines the detection pipeline, effectively removing the need for many hand …

Reconet: Recurrent correction network for fast and efficient multi-modality image fusion

Z Huang, J Liu, X Fan, R Liu, W Zhong… - European conference on …, 2022‏ - Springer
Recent advances in deep networks have gained great attention in infrared and visible image
fusion (IVIF). Nevertheless, most existing methods are incapable of dealing with slight …

Probabilistic anchor assignment with iou prediction for object detection

K Kim, HS Lee - Computer Vision–ECCV 2020: 16th European …, 2020‏ - Springer
In object detection, determining which anchors to assign as positive or negative samples,
known as anchor assignment, has been revealed as a core procedure that can significantly …