{"total":251,"rows":[{"id":"2209.15425","title":"Spikformer: When Spiking Neural Network Meets Transformer","created":"2022-09-29","cited_by_count":271,"area":null},{"id":"2206.01191","title":"EfficientFormer: Vision Transformers at MobileNet Speed","created":"2022-06-02","cited_by_count":241,"area":null},{"id":"2204.07143","title":"Neighborhood Attention Transformer","created":"2022-04-14","cited_by_count":239,"area":null},{"id":"2204.02287","title":"Rethinking Visual Geo-localization for Large-Scale Applications","created":"2022-04-05","cited_by_count":163,"area":null},{"id":"2212.08059","title":"Rethinking Vision Transformers for MobileNet Size and Speed","created":"2022-12-15","cited_by_count":121,"area":null},{"id":"2106.03650","title":"Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer","created":"2021-06-07","cited_by_count":115,"area":null},{"id":"2304.03410","title":"$R^{2}$Former: Unified $R$etrieval and $R$eranking Transformer for Place Recognition","created":"2023-04-06","cited_by_count":102,"area":null},{"id":"2105.12723","title":"Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding","created":"2021-05-26","cited_by_count":97,"area":null},{"id":"2204.03444","title":"Deep Visual Geo-localization Benchmark","created":"2022-04-07","cited_by_count":84,"area":null},{"id":"2210.12843","title":"Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification","created":"2022-10-23","cited_by_count":65,"area":null},{"id":"2205.14258","title":"On the Symmetries of Deep Learning Models and their Internal Representations","created":"2022-05-27","cited_by_count":64,"area":null},{"id":"2209.15001","title":"Dilated Neighborhood Attention Transformer","created":"2022-09-29","cited_by_count":64,"area":null},{"id":"2112.12782","title":"SeMask: Semantically Masked Transformers for Semantic Segmentation","created":"2021-12-23","cited_by_count":55,"area":null},{"id":"2305.09828","title":"Mimetic Initialization of Self-Attention Layers","created":"2023-05-16","cited_by_count":54,"area":null},{"id":"2303.04743","title":"Vector Quantized Time Series Generation with a Bidirectional Prior Model","created":"2023-03-08","cited_by_count":50,"area":null},{"id":"2302.03548","title":"PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer","created":"2023-02-07","cited_by_count":48,"area":null},{"id":"2108.03990","title":"TriTransNet: RGB-D Salient Object Detection with a Triplet Transformer Embedding Network","created":"2021-08-09","cited_by_count":45,"area":null},{"id":"2205.10920","title":"Test-Time Robust Personalization for Federated Learning","created":"2022-05-22","cited_by_count":39,"area":null},{"id":"2109.04454","title":"ConvMLP: Hierarchical Convolutional MLPs for Vision","created":"2021-09-09","cited_by_count":37,"area":null},{"id":"2205.13462","title":"FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction","created":"2022-05-26","cited_by_count":35,"area":null},{"id":"2210.02326","title":"Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning","created":"2022-10-05","cited_by_count":35,"area":null},{"id":"2308.08333","title":"Improving Depth Gradient Continuity in Transformers: A Comparative Study on Monocular Depth Estimation with CNN","created":"2023-08-16","cited_by_count":35,"area":null},{"id":"2106.02105","title":"A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks","created":"2021-06-03","cited_by_count":34,"area":null},{"id":"2207.10026","title":"Locality Guidance for Improving Vision Transformers on Tiny Datasets","created":"2022-07-20","cited_by_count":33,"area":null},{"id":"2206.00566","title":"The Fully Convolutional Transformer for Medical Image Segmentation","created":"2022-06-01","cited_by_count":32,"area":null},{"id":"2302.07173","title":"An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning","created":"2023-02-14","cited_by_count":32,"area":null},{"id":"2401.02020","title":"Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket","created":"2024-01-04","cited_by_count":30,"area":null},{"id":"2205.12141","title":"One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks","created":"2022-05-24","cited_by_count":29,"area":null},{"id":"2210.05958","title":"Bridging the Gap Between Vision Transformers and Convolutional Neural Networks on Small Datasets","created":"2022-10-12","cited_by_count":29,"area":null},{"id":"2110.02180","title":"Noisy Feature Mixup","created":"2021-10-05","cited_by_count":27,"area":null},{"id":"2210.07562","title":"TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers","created":"2022-10-14","cited_by_count":26,"area":null},{"id":"2207.03868","title":"Learning Sequential Descriptors for Sequence-based Visual Place Recognition","created":"2022-07-08","cited_by_count":25,"area":null},{"id":"2301.12149","title":"POSTER++: A simpler and stronger facial expression recognition network","created":"2023-01-28","cited_by_count":25,"area":null},{"id":"2209.14105","title":"Exploring the Relationship between Architecture and Adversarially Robust Generalization","created":"2022-09-28","cited_by_count":23,"area":null},{"id":"2204.01186","title":"Revisiting a kNN-based Image Classification System with High-capacity Storage","created":"2022-04-03","cited_by_count":22,"area":null},{"id":"2207.13516","title":"Online Continual Learning with Contrastive Vision Transformer","created":"2022-07-24","cited_by_count":21,"area":null},{"id":"2408.08284","title":"Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning","created":"2024-08-15","cited_by_count":21,"area":null},{"id":"2205.12466","title":"Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning","created":"2022-05-25","cited_by_count":20,"area":null},{"id":"2208.12801","title":"VMFormer: End-to-End Video Matting with Transformer","created":"2022-08-26","cited_by_count":20,"area":null},{"id":"2211.13955","title":"MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention","created":"2022-11-25","cited_by_count":20,"area":null},{"id":"2202.11781","title":"RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-guided Disease Classification","created":"2022-02-23","cited_by_count":19,"area":null},{"id":"2205.14375","title":"WaveMix: A Resource-efficient Neural Network for Image Analysis","created":"2022-05-28","cited_by_count":19,"area":null},{"id":"2211.10686","title":"Spikeformer: A Novel Architecture for Training High-Performance Low-Latency Spiking Neural Network","created":"2022-11-19","cited_by_count":19,"area":null},{"id":"2403.01944","title":"Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification","created":"2024-03-04","cited_by_count":18,"area":null},{"id":"2211.05770","title":"Efficient Image Generation with Variadic Attention Heads","created":"2022-11-10","cited_by_count":17,"area":null},{"id":"2203.14679","title":"Brain-inspired Multilayer Perceptron with Spiking Neurons","created":"2022-03-28","cited_by_count":16,"area":null},{"id":"2202.11921","title":"Auto-scaling Vision Transformers without Training","created":"2022-02-24","cited_by_count":15,"area":null},{"id":"2403.03385","title":"Multi-modal Deep Learning","created":"2024-03-06","cited_by_count":15,"area":null},{"id":"2310.12956","title":"Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems","created":"2023-10-19","cited_by_count":14,"area":null},{"id":"2405.16397","title":"AdaFisher: Adaptive Second Order Optimization via Fisher Information","created":"2024-05-26","cited_by_count":14,"area":null},{"id":"2204.03163","title":"Low-Dose CT Denoising via Sinogram Inner-Structure Transformer","created":"2022-04-07","cited_by_count":13,"area":null},{"id":"2208.02611","title":"Surgical Skill Assessment via Video Semantic Aggregation","created":"2022-08-04","cited_by_count":13,"area":null},{"id":"2309.05015","title":"DeViT: Decomposing Vision Transformers for Collaborative Inference in Edge Devices","created":"2023-09-10","cited_by_count":13,"area":null},{"id":"2404.01775","title":"A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?","created":"2024-04-02","cited_by_count":13,"area":null},{"id":"2206.10844","title":"Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices","created":"2022-06-22","cited_by_count":12,"area":null},{"id":"2207.08569","title":"Multi-manifold Attention for Vision Transformers","created":"2022-07-18","cited_by_count":12,"area":null},{"id":"2210.08066","title":"Optimizing Vision Transformers for Medical Image Segmentation","created":"2022-10-14","cited_by_count":12,"area":null},{"id":"2211.17161","title":"Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification","created":"2022-11-30","cited_by_count":12,"area":null},{"id":"2304.11335","title":"Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style Transfers","created":"2023-04-22","cited_by_count":12,"area":null},{"id":"2307.03493","title":"ITA: An Energy-Efficient Attention and Softmax Accelerator for Quantized Transformers","created":"2023-07-07","cited_by_count":12,"area":null},{"id":"2109.14382","title":"UFO-ViT: High Performance Linear Vision Transformer without Softmax","created":"2021-09-29","cited_by_count":11,"area":null},{"id":"2301.11125","title":"A benchmark for toxic comment classification on Civil Comments dataset","created":"2023-01-26","cited_by_count":11,"area":null},{"id":"2403.00729","title":"Can Transformers Capture Spatial Relations between Objects?","created":"2024-03-01","cited_by_count":11,"area":null},{"id":"2108.09598","title":"SERF: Towards better training of deep neural networks using log-Softplus ERror activation Function","created":"2021-08-21","cited_by_count":10,"area":null},{"id":"2205.09995","title":"Mask-guided Vision Transformer (MG-ViT) for Few-Shot Learning","created":"2022-05-20","cited_by_count":10,"area":null},{"id":"2208.00777","title":"D3Former: Debiased Dual Distilled Transformer for Incremental Learning","created":"2022-07-25","cited_by_count":10,"area":null},{"id":"2209.09070","title":"SOCRATES: A Stereo Camera Trap for Monitoring of Biodiversity","created":"2022-09-19","cited_by_count":10,"area":null},{"id":"2210.13889","title":"Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data","created":"2022-10-25","cited_by_count":10,"area":null},{"id":"2303.09730","title":"ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices","created":"2023-03-17","cited_by_count":10,"area":null},{"id":"2304.11954","title":"Spikingformer: A Key Foundation Model for Spiking Neural Networks","created":"2023-04-24","cited_by_count":10,"area":null},{"id":"2312.16045","title":"Algebraic Positional Encodings","created":"2023-12-26","cited_by_count":10,"area":null},{"id":"2203.03689","title":"WaveMix: Resource-efficient Token Mixing for Images","created":"2022-03-07","cited_by_count":9,"area":null},{"id":"2208.06643","title":"Recent Progress in Transformer-based Medical Image Analysis","created":"2022-08-13","cited_by_count":9,"area":null},{"id":"2305.01666","title":"BrainNPT: Pre-training of Transformer networks for brain network classification","created":"2023-05-02","cited_by_count":9,"area":null},{"id":"2310.05184","title":"AANet: Aggregation and Alignment Network with Semi-hard Positive Sample Mining for Hierarchical Place Recognition","created":"2023-10-08","cited_by_count":9,"area":null},{"id":"2312.05705","title":"Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC","created":"2023-12-09","cited_by_count":9,"area":null},{"id":"2111.10866","title":"CpT: Convolutional Point Transformer for 3D Point Cloud Processing","created":"2021-11-21","cited_by_count":8,"area":null},{"id":"2304.11450","title":"Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach using a Dilated Transformer and U-Net Architecture","created":"2023-04-22","cited_by_count":8,"area":null},{"id":"2403.19787","title":"JIST: Joint Image and Sequence Training for Sequential Visual Place Recognition","created":"2024-03-28","cited_by_count":8,"area":null},{"id":"2409.03901","title":"Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT Models","created":"2024-09-05","cited_by_count":8,"area":null},{"id":"2108.07153","title":"Escaping the Gradient Vanishing: Periodic Alternatives of Softmax in Attention Mechanism","created":"2021-08-16","cited_by_count":7,"area":null},{"id":"2112.08798","title":"Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation","created":"2021-12-16","cited_by_count":7,"area":null},{"id":"2207.03041","title":"Vision Transformers: State of the Art and Research Challenges","created":"2022-07-07","cited_by_count":7,"area":null},{"id":"2312.02843","title":"Are Vision Transformers More Data Hungry Than Newborn Visual Systems?","created":"2023-12-05","cited_by_count":7,"area":null},{"id":"2401.13987","title":"Cross-Domain Few-Shot Learning via Adaptive Transformer Networks","created":"2024-01-25","cited_by_count":7,"area":null},{"id":"2405.02081","title":"A Mutual Information Perspective on Federated Contrastive Learning","created":"2024-05-03","cited_by_count":7,"area":null},{"id":"2405.14569","title":"PrivCirNet: Efficient Private Inference via Block Circulant Transformation","created":"2024-05-23","cited_by_count":7,"area":null},{"id":"2410.21615","title":"NYC-Event-VPR: A Large-Scale High-Resolution Event-Based Visual Place Recognition Dataset in Dense Urban Environments","created":"2024-10-28","cited_by_count":7,"area":null},{"id":"2106.10452","title":"MSN: Efficient Online Mask Selection Network for Video Instance Segmentation","created":"2021-06-19","cited_by_count":6,"area":null},{"id":"2302.03023","title":"V1T: large-scale mouse V1 response prediction using a Vision Transformer","created":"2023-02-06","cited_by_count":6,"area":null},{"id":"2304.05350","title":"Astroformer: More Data Might not be all you need for Classification","created":"2023-04-03","cited_by_count":6,"area":null},{"id":"2305.11467","title":"Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition","created":"2023-05-19","cited_by_count":6,"area":null},{"id":"2308.11357","title":"Exemplar-Free Continual Transformer with Convolutions","created":"2023-08-22","cited_by_count":6,"area":null},{"id":"2404.05196","title":"HSViT: Horizontally Scalable Vision Transformer","created":"2024-04-08","cited_by_count":6,"area":null},{"id":"2406.05612","title":"Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision","created":"2024-06-09","cited_by_count":6,"area":null},{"id":"2407.14616","title":"DeepCA: Deep Learning-based 3D Coronary Artery Tree Reconstruction from Two 2D Non-simultaneous X-ray Angiography Projections","created":"2024-07-19","cited_by_count":6,"area":null},{"id":"2501.12900","title":"Unified CNNs and transformers underlying learning mechanism reveals multi-head attention modus vivendi","created":"2025-01-22","cited_by_count":6,"area":null},{"id":"2108.03414","title":"Vision Transformer for femur fracture classification","created":"2021-08-07","cited_by_count":5,"area":null},{"id":"2201.10271","title":"Convolutional Xformers for Vision","created":"2022-01-25","cited_by_count":5,"area":null},{"id":"2204.12143","title":"Deeper Insights into the Robustness of ViTs towards Common Corruptions","created":"2022-04-26","cited_by_count":5,"area":null}],"next_cursor":"100"}