{"total":78,"rows":[{"id":"2210.08823","title":"Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning","created":"2022-10-17","cited_by_count":294,"area":null},{"id":"2303.08810","title":"BiFormer: Vision Transformer with Bi-Level Routing Attention","created":"2023-03-15","cited_by_count":151,"area":null},{"id":"2210.13452","title":"MetaFormer Baselines for Vision","created":"2022-10-24","cited_by_count":132,"area":null},{"id":"2210.16774","title":"Dataset Distillation via Factorization","created":"2022-10-30","cited_by_count":115,"area":null},{"id":"2303.16900","title":"InceptionNeXt: When Inception Meets ConvNeXt","created":"2023-03-29","cited_by_count":86,"area":null},{"id":"2304.02419","title":"TM2D: Bimodality Driven 3D Dance Generation via Music-Text Integration","created":"2023-04-05","cited_by_count":76,"area":null},{"id":"2309.11523","title":"RMT: Retentive Networks Meet Vision Transformers","created":"2023-09-20","cited_by_count":68,"area":null},{"id":"2407.02158","title":"UltraPixel: Advancing Ultra-High-Resolution Image Synthesis to New Peaks","created":"2024-07-02","cited_by_count":65,"area":null},{"id":"2207.03337","title":"Factorizing Knowledge in Neural Networks","created":"2022-07-04","cited_by_count":59,"area":null},{"id":"2206.06293","title":"Learning Domain Adaptive Object Detection with Probabilistic Teacher","created":"2022-06-13","cited_by_count":57,"area":null},{"id":"2208.04464","title":"In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation","created":"2022-08-08","cited_by_count":51,"area":null},{"id":"2307.08579","title":"Scale-Aware Modulation Meet Transformer","created":"2023-07-17","cited_by_count":49,"area":null},{"id":"2401.15855","title":"Cross-Scale MAE: A Tale of Multi-Scale Exploitation in Remote Sensing","created":"2024-01-29","cited_by_count":47,"area":null},{"id":"2211.11167","title":"Vision Transformer with Super Token Sampling","created":"2022-11-21","cited_by_count":44,"area":null},{"id":"2207.05621","title":"MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing","created":"2022-07-12","cited_by_count":39,"area":null},{"id":"2302.01791","title":"DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition","created":"2023-02-03","cited_by_count":34,"area":null},{"id":"2308.12216","title":"SG-Former: Self-guided Transformer with Evolving Token Reallocation","created":"2023-08-23","cited_by_count":32,"area":null},{"id":"2411.07635","title":"Breaking the Low-Rank Dilemma of Linear Attention","created":"2024-11-12","cited_by_count":31,"area":null},{"id":"2207.08224","title":"Learning with Recoverable Forgetting","created":"2022-07-17","cited_by_count":30,"area":null},{"id":"2402.12788","title":"RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention","created":"2024-02-20","cited_by_count":30,"area":null},{"id":"2207.11681","title":"Learning Graph Neural Networks for Image Style Transfer","created":"2022-07-24","cited_by_count":29,"area":null},{"id":"2210.04206","title":"Attention Diversification for Domain Generalization","created":"2022-10-09","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":"2206.09325","title":"EATFormer: Improving Vision Transformer Inspired by Evolutionary Algorithm","created":"2022-06-19","cited_by_count":27,"area":null},{"id":"2306.00396","title":"Lightweight Vision Transformer with Bidirectional Interaction","created":"2023-06-01","cited_by_count":25,"area":null},{"id":"2207.06124","title":"DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation","created":"2022-07-13","cited_by_count":24,"area":null},{"id":"2301.01296","title":"TinyMIM: An Empirical Study of Distilling MIM Pre-trained Models","created":"2023-01-03","cited_by_count":24,"area":null},{"id":"2301.04648","title":"Head-Free Lightweight Semantic Segmentation with Linear Transformer","created":"2023-01-11","cited_by_count":22,"area":null},{"id":"2309.13700","title":"Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation","created":"2023-09-24","cited_by_count":21,"area":null},{"id":"2310.19380","title":"TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition","created":"2023-10-30","cited_by_count":21,"area":null},{"id":"2404.16573","title":"Multi-Scale Representations by Varying Window Attention for Semantic Segmentation","created":"2024-04-25","cited_by_count":20,"area":null},{"id":"2308.13998","title":"Computation-efficient Deep Learning for Computer Vision: A Survey","created":"2023-08-27","cited_by_count":14,"area":null},{"id":"2407.17261","title":"Embedding-Free Transformer with Inference Spatial Reduction for Efficient Semantic Segmentation","created":"2024-07-24","cited_by_count":14,"area":null},{"id":"2205.11397","title":"Super Vision Transformer","created":"2022-05-23","cited_by_count":13,"area":null},{"id":"2209.02197","title":"LRT: An Efficient Low-Light Restoration Transformer for Dark Light Field Images","created":"2022-09-06","cited_by_count":12,"area":null},{"id":"2212.06795","title":"GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation","created":"2022-12-13","cited_by_count":11,"area":null},{"id":"2311.15157","title":"Advancing Vision Transformers with Group-Mix Attention","created":"2023-11-26","cited_by_count":11,"area":null},{"id":"2212.12977","title":"SMMix: Self-Motivated Image Mixing for Vision Transformers","created":"2022-12-26","cited_by_count":8,"area":null},{"id":"2206.11073","title":"A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers","created":"2022-05-20","cited_by_count":7,"area":null},{"id":"2302.12416","title":"A Convolutional Vision Transformer for Semantic Segmentation of Side-Scan Sonar Data","created":"2023-02-24","cited_by_count":7,"area":null},{"id":"2208.13138","title":"ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers","created":"2022-08-28","cited_by_count":6,"area":null},{"id":"2404.02585","title":"Unsegment Anything by Simulating Deformation","created":"2024-04-03","cited_by_count":6,"area":null},{"id":"2405.13335","title":"Vision Transformer with Sparse Scan Prior","created":"2024-05-22","cited_by_count":6,"area":null},{"id":"2503.08726","title":"SIMAC: A Semantic-Driven Integrated Multimodal Sensing And Communication Framework","created":"2025-03-11","cited_by_count":6,"area":null},{"id":"2207.11789","title":"Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection","created":"2022-07-24","cited_by_count":5,"area":null},{"id":"2304.03481","title":"PSLT: A Light-weight Vision Transformer with Ladder Self-Attention and Progressive Shift","created":"2023-04-07","cited_by_count":5,"area":null},{"id":"2307.10642","title":"RetouchingFFHQ: A Large-scale Dataset for Fine-grained Face Retouching Detection","created":"2023-07-20","cited_by_count":5,"area":null},{"id":"2312.08614","title":"Factorization Vision Transformer: Modeling Long Range Dependency with Local Window Cost","created":"2023-12-14","cited_by_count":5,"area":null},{"id":"2405.15160","title":"ARVideo: Autoregressive Pretraining for Self-Supervised Video Representation Learning","created":"2024-05-24","cited_by_count":5,"area":null},{"id":"2406.15320","title":"Rethinking Remote Sensing Change Detection With A Mask View","created":"2024-06-21","cited_by_count":5,"area":null},{"id":"2312.06136","title":"BACTrack: Building Appearance Collection for Aerial Tracking","created":"2023-12-11","cited_by_count":4,"area":null},{"id":"2410.08582","title":"DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention","created":"2024-10-11","cited_by_count":4,"area":null},{"id":"2412.11458","title":"HResFormer: Hybrid Residual Transformer for Volumetric Medical Image Segmentation","created":"2024-12-16","cited_by_count":4,"area":null},{"id":"2301.06869","title":"SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation","created":"2023-01-17","cited_by_count":3,"area":null},{"id":"2304.00502","title":"CNNs with Multi-Level Attention for Domain Generalization","created":"2023-04-02","cited_by_count":3,"area":null},{"id":"2308.05872","title":"Vision Backbone Enhancement via Multi-Stage Cross-Scale Attention","created":"2023-08-10","cited_by_count":3,"area":null},{"id":"2308.12894","title":"Boosting Semantic Segmentation from the Perspective of Explicit Class Embeddings","created":"2023-08-24","cited_by_count":3,"area":null},{"id":"2401.11718","title":"MsSVT++: Mixed-scale Sparse Voxel Transformer with Center Voting for 3D Object Detection","created":"2024-01-22","cited_by_count":3,"area":null},{"id":"2402.11303","title":"FViT: A Focal Vision Transformer with Gabor Filter","created":"2024-02-17","cited_by_count":3,"area":null},{"id":"2508.09000","title":"UniConvNet: Expanding Effective Receptive Field while Maintaining Asymptotically Gaussian Distribution for ConvNets of Any Scale","created":"2025-08-12","cited_by_count":3,"area":null},{"id":"2401.04403","title":"MST: Adaptive Multi-Scale Tokens Guided Interactive Segmentation","created":"2024-01-09","cited_by_count":2,"area":null},{"id":"2409.08501","title":"PSTNet: Enhanced Polyp Segmentation with Multi-scale Alignment and Frequency Domain Integration","created":"2024-09-13","cited_by_count":2,"area":null},{"id":"2503.12783","title":"Mixed-granularity Implicit Representation for Continuous Hyperspectral Compressive Reconstruction","created":"2025-03-17","cited_by_count":2,"area":null},{"id":"2504.09088","title":"Multi-Modal Brain Tumor Segmentation via 3D Multi-Scale Self-attention and Cross-attention","created":"2025-04-12","cited_by_count":2,"area":null},{"id":"2505.03113","title":"Image Recognition with Online Lightweight Vision Transformer: A Survey","created":"2025-05-06","cited_by_count":2,"area":null},{"id":"2211.03140","title":"MSMG-Net: Multi-scale Multi-grained Supervised Metworks for Multi-task Image Manipulation Detection and Localization","created":"2022-11-06","cited_by_count":1,"area":null},{"id":"2309.12639","title":"CINFormer: Transformer network with multi-stage CNN feature injection for surface defect segmentation","created":"2023-09-22","cited_by_count":1,"area":null},{"id":"2309.17399","title":"IFAST: Weakly Supervised Interpretable Face Anti-spoofing from Single-shot Binocular NIR Images","created":"2023-09-29","cited_by_count":1,"area":null},{"id":"2508.16884","title":"A Lightweight Convolution and Vision Transformer integrated model with Multi-scale Self-attention Mechanism","created":"2025-08-23","cited_by_count":1,"area":null},{"id":"2301.02650","title":"Hierarchical Point Attention for Indoor 3D Object Detection","created":"2023-01-06","cited_by_count":0,"area":null},{"id":"2303.09988","title":"Star-Net: Improving Single Image Desnowing Model With More Efficient Connection and Diverse Feature Interaction","created":"2023-03-17","cited_by_count":0,"area":null},{"id":"2303.17815","title":"APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding","created":"2023-03-31","cited_by_count":0,"area":null},{"id":"2306.01929","title":"Recent Advances of Local Mechanisms in Computer Vision: A Survey and Outlook of Recent Work","created":"2023-06-02","cited_by_count":0,"area":null},{"id":"2307.14588","title":"MCPA: Multi-scale Cross Perceptron Attention Network for 2D Medical Image Segmentation","created":"2023-07-27","cited_by_count":0,"area":null},{"id":"2409.06963","title":"Brain-Inspired Stepwise Patch Merging for Vision Transformers","created":"2024-09-11","cited_by_count":0,"area":null},{"id":"2412.02197","title":"Cascaded Multi-Scale Attention for Enhanced Multi-Scale Feature Extraction and Interaction with Low-Resolution Images","created":"2024-12-03","cited_by_count":0,"area":null},{"id":"2504.09106","title":"Multi-modal and Multi-view Fundus Image Fusion for Retinopathy Diagnosis via Multi-scale Cross-attention and Shifted Window Self-attention","created":"2025-04-12","cited_by_count":0,"area":null},{"id":"2506.16369","title":"Prompt-based Dynamic Token Pruning for Efficient Segmentation of Medical Images","created":"2025-06-19","cited_by_count":0,"area":null}],"next_cursor":null}