{"total":61,"rows":[{"id":"2105.15203","title":"SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers","created":"2021-05-31","cited_by_count":2940,"area":null},{"id":"2102.04906","title":"Dynamic Neural Networks: A Survey","created":"2021-02-09","cited_by_count":408,"area":null},{"id":"2105.02358","title":"Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks","created":"2021-05-05","cited_by_count":109,"area":null},{"id":"2203.05898","title":"Hyperbolic Image Segmentation","created":"2022-03-11","cited_by_count":102,"area":null},{"id":"2106.03149","title":"Large-scale Unsupervised Semantic Segmentation","created":"2021-06-06","cited_by_count":101,"area":null},{"id":"2109.04553","title":"Is Attention Better Than Matrix Decomposition?","created":"2021-09-09","cited_by_count":77,"area":null},{"id":"2401.17868","title":"Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model","created":"2024-01-31","cited_by_count":69,"area":null},{"id":"2204.12077","title":"AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images","created":"2022-04-26","cited_by_count":43,"area":null},{"id":"2107.00782","title":"Polarized Self-Attention: Towards High-quality Pixel-wise Regression","created":"2021-07-02","cited_by_count":39,"area":null},{"id":"2103.17235","title":"FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation","created":"2021-03-31","cited_by_count":36,"area":null},{"id":"2105.10886","title":"VS-Net: Voting with Segmentation for Visual Localization","created":"2021-05-23","cited_by_count":29,"area":null},{"id":"2306.02061","title":"Balancing Logit Variation for Long-tailed Semantic Segmentation","created":"2023-06-03","cited_by_count":26,"area":null},{"id":"2310.18954","title":"Mask Propagation for Efficient Video Semantic Segmentation","created":"2023-10-29","cited_by_count":26,"area":null},{"id":"2204.03330","title":"Learning Local and Global Temporal Contexts for Video Semantic Segmentation","created":"2022-04-07","cited_by_count":24,"area":null},{"id":"2208.10159","title":"Prompt-Matched Semantic Segmentation","created":"2022-08-22","cited_by_count":22,"area":null},{"id":"2111.00454","title":"Gaussian Kernel Mixture Network for Single Image Defocus Deblurring","created":"2021-10-31","cited_by_count":20,"area":null},{"id":"2310.13026","title":"Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation Models","created":"2023-10-19","cited_by_count":19,"area":null},{"id":"2105.14447","title":"EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional Neural Network","created":"2021-05-30","cited_by_count":15,"area":null},{"id":"2202.00432","title":"Continual Attentive Fusion for Incremental Learning in Semantic Segmentation","created":"2022-02-01","cited_by_count":15,"area":null},{"id":"2208.14143","title":"FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation","created":"2022-08-30","cited_by_count":14,"area":"distill"},{"id":"2402.02941","title":"Exploring the Synergies of Hybrid CNNs and ViTs Architectures for Computer Vision: A survey","created":"2024-02-05","cited_by_count":13,"area":null},{"id":"2202.07242","title":"Neural Architecture Search for Dense Prediction Tasks in Computer Vision","created":"2022-02-15","cited_by_count":12,"area":null},{"id":"2208.14241","title":"Boosting Night-time Scene Parsing with Learnable Frequency","created":"2022-08-30","cited_by_count":9,"area":null},{"id":"2106.08382","title":"DMSANet: Dual Multi Scale Attention Network","created":"2021-06-13","cited_by_count":8,"area":null},{"id":"2107.13154","title":"Global Aggregation then Local Distribution for Scene Parsing","created":"2021-07-28","cited_by_count":8,"area":null},{"id":"2206.04879","title":"Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion","created":"2022-06-10","cited_by_count":8,"area":null},{"id":"2211.02915","title":"ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation","created":"2022-11-05","cited_by_count":7,"area":null},{"id":"2209.12468","title":"RetiFluidNet: A Self-Adaptive and Multi-Attention Deep Convolutional Network for Retinal OCT Fluid Segmentation","created":"2022-09-26","cited_by_count":6,"area":null},{"id":"2311.13409","title":"CompenHR: Efficient Full Compensation for High-resolution Projector","created":"2023-11-22","cited_by_count":6,"area":null},{"id":"2212.14306","title":"Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models","created":"2022-12-29","cited_by_count":5,"area":"diffusion"},{"id":"2305.00671","title":"PRSeg: A Lightweight Patch Rotate MLP Decoder for Semantic Segmentation","created":"2023-05-01","cited_by_count":4,"area":null},{"id":"2308.12320","title":"Understanding Dark Scenes by Contrasting Multi-Modal Observations","created":"2023-08-23","cited_by_count":4,"area":null},{"id":"2208.10491","title":"Improving Speech Emotion Recognition Through Focus and Calibration Attention Mechanisms","created":"2022-08-21","cited_by_count":3,"area":null},{"id":"2212.04227","title":"Self-training via Metric Learning for Source-Free Domain Adaptation of Semantic Segmentation","created":"2022-12-08","cited_by_count":3,"area":null},{"id":"2304.09059","title":"Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation","created":"2023-04-18","cited_by_count":3,"area":null},{"id":"2403.12767","title":"Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation","created":"2024-03-19","cited_by_count":3,"area":null},{"id":"2103.03510","title":"Variational Structured Attention Networks for Deep Visual Representation Learning","created":"2021-03-05","cited_by_count":2,"area":null},{"id":"2111.06812","title":"Sci-Net: Scale Invariant Model for Buildings Segmentation from Aerial Imagery","created":"2021-11-12","cited_by_count":2,"area":null},{"id":"2111.09976","title":"M2A: Motion Aware Attention for Accurate Video Action Recognition","created":"2021-11-18","cited_by_count":2,"area":null},{"id":"2305.08462","title":"Not All Pixels Are Equal: Learning Pixel Hardness for Semantic Segmentation","created":"2023-05-15","cited_by_count":2,"area":null},{"id":"2309.00871","title":"Boosting Weakly-Supervised Image Segmentation via Representation, Transform, and Compensator","created":"2023-09-02","cited_by_count":2,"area":null},{"id":"2406.03478","title":"Convolutional Neural Networks and Vision Transformers for Fashion MNIST Classification: A Literature Review","created":"2024-06-05","cited_by_count":2,"area":null},{"id":"2411.17061","title":"SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation","created":"2024-11-26","cited_by_count":2,"area":null},{"id":"2104.01792","title":"Hierarchical Pyramid Representations for Semantic Segmentation","created":"2021-04-05","cited_by_count":1,"area":null},{"id":"2104.02533","title":"DCANet: Dense Context-Aware Network for Semantic Segmentation","created":"2021-04-06","cited_by_count":1,"area":null},{"id":"2204.06747","title":"Unsupervised Domain Adaptation with Implicit Pseudo Supervision for Semantic Segmentation","created":"2022-04-14","cited_by_count":1,"area":null},{"id":"2306.03497","title":"Instructive Feature Enhancement for Dichotomous Medical Image Segmentation","created":"2023-06-06","cited_by_count":1,"area":null},{"id":"2311.03071","title":"OrthoNets: Orthogonal Channel Attention Networks","created":"2023-11-06","cited_by_count":1,"area":null},{"id":"2311.15625","title":"Only Positive Cases: 5-fold High-order Attention Interaction Model for Skin Segmentation Derived Classification","created":"2023-11-27","cited_by_count":1,"area":null},{"id":"2407.01328","title":"CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving Scenes","created":"2024-07-01","cited_by_count":1,"area":null},{"id":"2103.04990","title":"Use square root affinity to regress labels in semantic segmentation","created":"2021-03-07","cited_by_count":0,"area":null},{"id":"2107.09909","title":"DRDF: Determining the Importance of Different Multimodal Information with Dual-Router Dynamic Framework","created":"2021-07-21","cited_by_count":0,"area":null},{"id":"2109.02084","title":"(M)SLAe-Net: Multi-Scale Multi-Level Attention embedded Network for Retinal Vessel Segmentation","created":"2021-09-05","cited_by_count":0,"area":null},{"id":"2304.05448","title":"Scale-Space Hypernetworks for Efficient Biomedical Imaging","created":"2023-04-11","cited_by_count":0,"area":null},{"id":"2309.15850","title":"Reflection Invariance Learning for Few-shot Semantic Segmentation","created":"2023-06-01","cited_by_count":0,"area":null},{"id":"2310.00919","title":"BAAF: A benchmark attention adaptive framework for medical ultrasound image segmentation tasks","created":"2023-10-02","cited_by_count":0,"area":null},{"id":"2410.02129","title":"DMC-Net: Lightweight Dynamic Multi-Scale and Multi-Resolution Convolution Network for Pancreas Segmentation in CT Images","created":"2024-10-03","cited_by_count":0,"area":null},{"id":"2503.08290","title":"SegDesicNet: Lightweight Semantic Segmentation in Remote Sensing with Geo-Coordinate Embeddings for Domain Adaptation","created":"2025-03-11","cited_by_count":0,"area":null},{"id":"2512.01657","title":"DB-KAUNet: An Adaptive Dual Branch Kolmogorov-Arnold UNet for Retinal Vessel Segmentation","created":"2025-12-01","cited_by_count":0,"area":null},{"id":"2607.19378","title":"Native Multi-Dimensional Subquadratic Operators via Input Dependent Long Convolutions","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2610.15079","title":"Region Aware Squeeze-and-Excitation Networks for Image Segmentation","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}