Convolutional Networks

CVPR 2024arXiv:2303.16900

#2

InceptionNeXt: When Inception Meets ConvNeXt

Weihao Yu, Pan Zhou, Shuicheng Yan et al.

280

CVPR 2024arXiv:2401.06197

#3

Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications

Yuwen Xiong, Zhiqi Li, Yuntao Chen et al.

148

CVPR 2024arXiv:2403.07589

#4

PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral Convolution

Honghao Chen, Xiangxiang Chu, Renyongjian et al.

68

ICLR 2024arXiv:2303.15919

#5

Fully Hyperbolic Convolutional Neural Networks for Computer Vision

Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

37

ICML 2024arXiv:2402.14730

#6

Clifford-Steerable Convolutional Neural Networks

Maksim Zhdanov, David Ruhe, Maurice Weiler et al.

equivariant convolutional networksclifford group neural networkspseudo-euclidean spacesmultivector fields+3

24

CVPR 2025arXiv:2503.00467

#7

Adaptive Rectangular Convolution for Remote Sensing Pansharpening

Xueyang Wang, Zhixin Zheng, Jiandong Shao et al.

adaptive rectangular convolutionremote sensing pansharpeningconvolutional neural networksscale-specific feature extraction+3

21

CVPR 2025arXiv:2503.23135

#8

LSNet: See Large, Focus Small

Ao Wang, Hui Chen, Zijia Lin et al.

lightweight vision networkslarge-kernel perceptionsmall-kernel aggregationefficient network design+3

21

CVPR 2025arXiv:2401.12736

#9

ShiftwiseConv: Small Convolutional Kernel with Large Kernel Effect

Dachong Li, li li, zhuangzhuang chen et al.

19

CVPR 2024arXiv:2403.19490

#10

Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment

Alireza Ganjdanesh, Shangqian Gao, Heng Huang

structural model pruningreinforcement learning agentjoint training pruningdynamic reward function+3

17

AAAI 2024arXiv:2403.08157

#11

CNN Kernels Can Be the Best Shapelets

Eric Qu, Yansen Wang, Xufang Luo et al.

Multiscale Low-Frequency Memory Network for Improved Feature Extraction in Convolutional Neural Networks

Fuzhi Wu, Jiasong Wu, Youyong Kong et al.

low-frequency informationconvolutional neural networksfeature extractionmultiscale memory network+4

10

AAAI 2024arXiv:2210.05742

#13

Curved Representation Space of Vision Transformers

Juyeop Kim, Junha Park, Songkuk Kim et al.

10

ICML 2024arXiv:2402.08010

#14

Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning

Yuxiao Wen, Arthur Jacot

convolutional bottleneck structurefeature learning dynamicsfrequency representation learningparameter norm scaling+4

9

CVPR 2025arXiv:2501.00603

#15

DiC: Rethinking Conv3x3 Designs in Diffusion Models

Yuchuan Tian, Jing Han, Chengcheng Wang et al.

diffusion modelsconvolutional architecturesimage generationtransformer architectures+4

8

neural implicit functionsconvolutional neural networksfrequency domain convolutionlarge kernel convolutions+3

#16

As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters

Margret Keuper, Julia Grabinski, Janis Keuper

ICLR 2025

8

ICLR 2025arXiv:2503.07674

#17

TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation

Chenghan Li, Mingchen LI, Ruisheng Diao

7

ICLR 2024arXiv:2401.14469

#18

Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels

Zahra Babaiee, Peyman Kiasari, Daniela Rus et al.

7

CVPR 2024arXiv:2403.06676

#19

CAM Back Again: Large Kernel CNNs from a Weakly Supervised Object Localization Perspective

Shunsuke Yasuki, Masato Taki

6

ICML 2025arXiv:2501.07930

#20

An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures

Thibaut Boissin, Franck Mamalet, Thomas Fel et al.

6

AAAI 2024arXiv:2312.12068

#21

PICNN: A Pathway towards Interpretable Convolutional Neural Networks

Wengang Guo, Jiayi Yang, HuiLin YIN et al.

interpretable convolutional networksfilter-class disentanglementbernoulli samplingreparameterization trick+3

5

ICLR 2025arXiv:2502.18538

#22

Revisiting Convolution Architecture in the Realm of DNA Foundation Models

Yu Bo, Weian Mao, Daniel Shao et al.

dna foundation modelsconvolutional networksdilated convolutionsgated convolutions+4

4

ICLR 2024arXiv:2403.15707

#23

Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs

Aakash Sunil Lahoti, Stefani Karp, Ezra Winston et al.

3

ICLR 2025arXiv:2412.09115

#24

Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations

Yudi Xie, Weichen Huang, Esther Alter et al.

ventral visual streamspatial latent estimationobject categorizationneural alignment+4

3

NEURIPS 2025arXiv:2505.21251

#25

Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework

Mustafa Hajij, Lennart Bastian, Sarah Osentoski et al.

receptive fieldslarge kernel cnnsvisual cortex alignmentlp-convolution+4

#26

Brain-inspired $L_p$-Convolution benefits large kernels and aligns better with visual cortex

Jea Kwon, Sungjun Lim, Kyungwoo Song et al.

ICLR 2025

ICLR 2025arXiv:2406.07843

#27

Self-Attention-Based Contextual Modulation Improves Neural System Identification

Isaac Lin, Tianye Wang, Shang Gao et al.

self-attention mechanismcontextual modulationneural system identificationvisual cortex modeling+3

ICCV 2025arXiv:2508.09000

#28

UniConvNet: Expanding Effective Receptive Field while Maintaining Asymptotically Gaussian Distribution for ConvNets of Any Scale

Yuhao Wang, Wei Xi

AAAI 2025arXiv:2412.16751

#29

The Master Key Filters Hypothesis: Deep Filters Are General

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus et al.

NEURIPS 2025arXiv:2412.06740

#30

Convolution Goes Higher-Order: A Biologically Inspired Mechanism Empowers Image Classification

Simone Azeglio, Olivier Marre, Peter Neri et al.

higher-order convolutionsimage classificationbiological visual processingvolterra expansion+4

NEURIPS 2025arXiv:2509.11711

#31

A Convolutional Neural Network Interpretable Framework for Human Ventral Visual Pathway Representation

Mufan Xue, Xinyu Wu, Jinlong Li et al.

The Quest for Universal Master Key Filters in DS-CNNs

Zahra Babaiee, Peyman M. Kiasari, Daniela Rus et al.

master key filtersdepthwise separable cnnsuniversal filter setconvolutional filter analysis+4

ICLR 2025arXiv:2410.04089

#33

Designing Concise ConvNets with Columnar Stages

Ashish Kumar, Jaesik Park

AAAI 2025arXiv:2409.13154

#34

Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities

Chengkun Sun, Jinqian Pan, Zhuoli Jin et al.

elimination singularitiesskip connection designpooling and unpoolingloss landscape analysis+4

NEURIPS 2025arXiv:2506.03089

#35

Explicitly Modeling Subcortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness

Lucas Piper, Arlindo L Oliveira, Tiago Marques