Convolutional Networks

SCTNet: Single Branch CNN with Transformer Semantic Information for Real-Time Segmentation

Authors: Zhengze Xu, Dongyue Wu, Changqian Yu et al.

MogaNet: Multi-order Gated Aggregation Network

Siyuan Li, Zedong Wang, Zicheng Liu et al.

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit

Blake Bordelon, Lorenzo Noci, Mufan Li et al.

Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurring

Xin Gao, Tianheng Qiu, Xinyu Zhang et al.

DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs

Donghyun Kim, Byeongho Heo, Dongyoon Han

Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization

Hancheng Min, Enrique Mallada, Rene Vidal

SAVSR: Arbitrary-Scale Video Super-resolution via a Learned Scale-Adaptive Network

Zekun Li, Hongying Liu, Fanhua Shang et al.

Hyper-Connections

Defa Zhu, Hongzhi Huang, Zihao Huang et al.

A Rainbow in Deep Network Black Boxes

Florentin Guth, Brice Ménard, Gaspar Rochette et al.

PARE-Net: Position-Aware Rotation-Equivariant Networks for Robust Point Cloud Registration

Runzhao Yao, Shaoyi Du, Wenting Cui et al.

Hybrid Proposal Refiner: Revisiting DETR Series from the Faster R-CNN Perspective

Jinjing Zhao, Fangyun Wei, Chang Xu

CNN Kernels Can Be the Best Shapelets

Eric Qu, Yansen Wang, Xufang Luo et al.

TopoNets: High performing vision and language models with brain-like topography

Mayukh Deb, Mainak Deb, Apurva Murty

Rethinking Features-Fused-Pyramid-Neck for Object Detection

Hulin Li

Multilinear Operator Networks

Yixin Cheng, Grigorios Chrysos, Markos Georgopoulos et al.

Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI

Sean I. Young, Yaël Balbastre, Bruce Fischl et al.

Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning

Tom Nuno Wolf, Fabian Bongratz, Anne-Marie Rickmann et al.

Residual Hyperbolic Graph Convolution Networks

Yangkai Xue, Jindou Dai, Zhipeng Lu et al.

ConDense: Consistent 2D-3D Pre-training for Dense and Sparse Features from Multi-View Images

Xiaoshuai Zhang, Zhicheng Wang, Howard Zhou et al.

Weight Conditioning for Smooth Optimization of Neural Networks

Hemanth Saratchandran, Thomas X Wang, Simon Lucey

Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN

Minsoo Kang, Minkoo Kang, Suhyun Kim

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks

Ziqing Wang, Yuetong Fang, Jiahang Cao et al.

How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning

Arthur Jacot, Seok Hoan Choi, Yuxiao Wen

Probing Equivariance and Symmetry Breaking in Convolutional Networks

Sharvaree Vadgama, Mohammad Islam, Domas Buracas et al.

FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion

Xiaofeng Wu, Velibor Bojkovic, Bin Gu et al.

Revisiting Calibration of Wide-Angle Radially Symmetric Cameras

Andrea Porfiri Dal Cin, Francesco Azzoni, Giacomo Boracchi et al.

DCT-CryptoNets: Scaling Private Inference in the Frequency Domain

Arjun Roy, Kaushik Roy

Spectral Convolutional Conditional Neural Process

Peiman Mohseni, Nick Duffield

PICNN: A Pathway towards Interpretable Convolutional Neural Networks

Wengang Guo, Jiayi Yang, HuiLin YIN et al.

Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks

Daniel Kunin, Giovanni Luca Marchetti, Feng Chen et al.

Scaling Convex Neural Networks with Burer-Monteiro Factorization

Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.

Revisiting Convolution Architecture in the Realm of DNA Foundation Models

Yu Bo, Weian Mao, Daniel Shao et al.

Transformative or Conservative? Conservation laws for ResNets and Transformers

Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré

Continuous Rotation Group Equivariant Network Inspired by Neural Population Coding

Zhiqiang Chen, Yang Chen, xiaolong Zou et al.

Targeted Activation Penalties Help CNNs Ignore Spurious Signals

Dekai Zhang, Matt Williams, Francesca Toni

Pick-or-Mix: Dynamic Channel Sampling for ConvNets

Ashish Kumar, Daneul Kim, Jaesik Park et al.

Learning Color Equivariant Representations

Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette

Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture

Sajad Movahedi, Antonio Orvieto, Seyed-Mohsen Moosavi-Dezfooli

Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework

Mustafa Hajij, Lennart Bastian, Sarah Osentoski et al.

Auto-Compressing Networks

Evangelos Dorovatas, Georgios Paraskevopoulos, Alexandros Potamianos

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

Yuhao Wang, Wei Xi

msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML

Zhaolan Huang, Emmanuel Baccelli

Deep Tree Tensor Networks

Chang Nie

Position: A Theory of Deep Learning Must Include Compositional Sparsity

David A. Danhofer, Davide DAscenzo, Rafael Dubach et al.

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

Simone Azeglio, Olivier Marre, Peter Neri et al.

Quantization-Friendly Winograd Transformations for Convolutional Neural Networks

Vladimir Protsenko, Vladimir Kryzhanovskiy, Alexander Filippov

Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding Networks for Image Compressive Sensing

Chen Liao, Yan Shen, Dan Li et al.

Metric Convolutions: A Unifying Theory to Adaptive Image Convolutions

Thomas Dagès, Michael Lindenbaum, Alfred Bruckstein

DεpS: Delayed ε-Shrinking for Faster Once-For-All Training

Aditya Annavajjala, Alind Khare, Animesh Agrawal et al.

Multiplication-Free Parallelizable Spiking Neurons with Efficient Spatio-Temporal Dynamics

Peng Xue, Wei Fang, Zhengyu Ma et al.

The Quest for Universal Master Key Filters in DS-CNNs

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

Enforcing Idempotency in Neural Networks

Nikolaj Jensen, Jamie Vicary

CODE-CL: Conceptor-Based Gradient Projection for Deep Continual Learning

Marco P. Apolinario, Sakshi Choudhary, Kaushik Roy

Neural Tangent Knowledge Distillation for Optical Convolutional Networks

Jinlin Xiang, Minho Choi, Yubo Zhang et al.

FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks

Quansong He, Xiangde Min, Kaishen Wang et al.

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

Lucas Piper, Arlindo L Oliveira, Tiago Marques

CPN: Complementary Proposal Network for Unconstrained Text Detection

Longhuang Wu, Shangxuan Tian, Youxin Wang et al.

Saliuitl: Ensemble Salience Guided Recovery of Adversarial Patches against CNNs

Mauricio Byrd Victorica, György Dán, Henrik Sandberg

DiCo: Revitalizing ConvNets for Scalable and Efficient Diffusion Modeling

Yuang Ai, Qihang Fan, Xuefeng Hu et al.

MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations

Yan Xie, Minrui Lv, Chen-Song Zhang

Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure

Can Pouliquen, Mathurin Massias, Titouan Vayer

Training the Untrainable: Introducing Inductive Bias via Representational Alignment

Vighnesh Subramaniam, David Mayo, Colin Conwell et al.

A Geometric Distortion Immunized Deep Watermarking Framework with Robustness Generalizability

Linfeng Ma, Han Fang, Tianyi Wei et al.

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

Yuxiao Wen, Arthur Jacot

On the VC dimension of deep group convolutional neural networks

Anna Sepliarskaia, Sophie Langer, Johannes Schmidt-Hieber

Towards Understanding Catastrophic Forgetting in Two-layer Convolutional Neural Networks

Boqi Li, Youjun Wang, Weiwei Liu

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

Jea Kwon, Sungjun Lim, Kyungwoo Song et al.

Inf-DiT: Upsampling any-resolution image with memory-efficient diffusion transformer.

Zhuoyi Yang, Heyang Jiang, Wenyi Hong et al.

Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design

Li, zhihao shu, Jie Ji et al.

One-dimensional Path Convolution

Xuanshu Luo, Martin Werner

Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers

Ekaterina Grishina, Mikhail Gorbunov, Maxim Rakhuba

An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures

Thibaut Boissin, Franck Mamalet, Thomas Fel et al.

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

Yudi Xie, Weichen Huang, Esther Alter et al.

On the Vulnerability of Skip Connections to Model Inversion Attacks

Jun Hao Koh, Sy-Tuyen Ho, Ngoc-Bao Nguyen et al.

FARSE-CNN: Fully Asynchronous, Recurrent and Sparse Event-Based CNN

Riccardo Santambrogio, Marco Cannici, Matteo Matteucci

Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods

Yuto Nishimura, Taiji Suzuki

HiDiffusion: Unlocking Higher-Resolution Creativity and Efficiency in Pretrained Diffusion Models

Shen Zhang, Zhaowei CHEN, Zhenyu Zhao et al.

CONDA: Condensed Deep Association Learning for Co-Salient Object Detection.

Long Li, Nian Liu, Dingwen Zhang et al.

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.

JPEG Inspired Deep Learning

Ahmed Hussien Salamah, Kaixiang Zheng, Yiwen Liu et al.

Efficient Training of Spiking Neural Networks with Multi-Parallel Implicit Stream Architecture

Zhigao Cao, Meng Li, Xiashuang Wang et al.

Fully Hyperbolic Convolutional Neural Networks for Computer Vision

Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

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

Chenghan Li, Mingchen LI, Ruisheng Diao

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

Margret Keuper, Julia Grabinski, Janis Keuper

Integer-Valued Training and Spike-driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection

Xinhao Luo, Man Yao, Yuhong Chou et al.

Normalize Filters! Classical Wisdom for Deep Vision

Gustavo Perez, Stella X. Yu

BaSIC: BayesNet Structure Learning for Computational Scalable Neural Image Compression

Yufeng Zhang, Hang Yu, Shizhan Liu et al.

Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training

Xiaochen Zhao, Chengting Yu, Kairong Yu et al.

Projective Equivariant Networks via Second-order Fundamental Differential Invariants

Yikang Li, Yeqing Qiu, Yuxuan Chen et al.

Rethinking Scale-Aware Temporal Encoding for Event-based Object Detection

Lin Zhu, Tengyu Long, Xiao Wang et al.

MobileODE: An Extra Lightweight Network

Le Yu, Jun Wu, Bo Gou et al.

Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels

Zahra Babaiee, Peyman Kiasari, Daniela Rus et al.

Spiking Neural Networks Need High-Frequency Information

Yuetong Fang, Deming Zhou, Ziqing Wang et al.

Towards the Resistance of Neural Network Fingerprinting to Fine-tuning

Ling Tang, YueFeng Chen, Hui Xue' et al.

QuadEnhancer: Leveraging Quadratic Transformations to Enhance Deep Neural Networks

Qian Chen, Linxin Yang, Akang Wang et al.

Unfolding-Associative Encoder-Decoder Network with Progressive Alignment for Pansharpening

Shijie Fang, Hongping Gan

CALM-PDE: Continuous and Adaptive Convolutions for Latent Space Modeling of Time-dependent PDEs

Jan Hagnberger, Daniel Musekamp, Mathias Niepert

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

From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics

Qinshuo Liu, Weiqin Zhao, Wei Huang et al.

Dimensionality Mismatch Between Brains and Artificial Neural Networks

Santiago Galella, Maren Wehrheim, Matthias Kaschube