{"total":55,"rows":[{"id":"2211.06220","title":"OneFormer: One Transformer to Rule Universal Image Segmentation","created":"2022-11-10","cited_by_count":328,"area":null},{"id":"2305.03045","title":"OctFormer: Octree-based Transformers for 3D Point Clouds","created":"2023-05-04","cited_by_count":109,"area":null},{"id":"2503.19108","title":"Your ViT is Secretly an Image Segmentation Model","created":"2025-03-24","cited_by_count":63,"area":null},{"id":"2404.10242","title":"Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology","created":"2024-04-16","cited_by_count":52,"area":null},{"id":"2412.06590","title":"Bridging the Divide: Reconsidering Softmax and Linear Attention","created":"2024-12-09","cited_by_count":48,"area":null},{"id":"2307.14008","title":"Adaptive Frequency Filters As Efficient Global Token Mixers","created":"2023-07-26","cited_by_count":45,"area":null},{"id":"2304.07803","title":"EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation","created":"2023-04-16","cited_by_count":43,"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":"2403.18819","title":"Benchmarking Object Detectors with COCO: A New Path Forward","created":"2024-03-27","cited_by_count":23,"area":null},{"id":"2211.09233","title":"Prompt Tuning for Parameter-efficient Medical Image Segmentation","created":"2022-11-16","cited_by_count":22,"area":null},{"id":"2309.01430","title":"DAT++: Spatially Dynamic Vision Transformer with Deformable Attention","created":"2023-09-04","cited_by_count":21,"area":null},{"id":"2504.16922","title":"Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light","created":"2025-04-23","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":"2311.07621","title":"To Transformers and Beyond: Large Language Models for the Genome","created":"2023-11-13","cited_by_count":15,"area":null},{"id":"2403.04690","title":"Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level","created":"2024-03-07","cited_by_count":14,"area":null},{"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":"2403.09065","title":"When Semantic Segmentation Meets Frequency Aliasing","created":"2024-03-14","cited_by_count":10,"area":null},{"id":"2407.21631","title":"RoadFormer+: Delivering RGB-X Scene Parsing through Scale-Aware Information Decoupling and Advanced Heterogeneous Feature Fusion","created":"2024-07-31","cited_by_count":10,"area":null},{"id":"2507.12006","title":"Frequency-Dynamic Attention Modulation for Dense Prediction","created":"2025-07-16","cited_by_count":10,"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":"2505.12742","title":"MVAR: Visual Autoregressive Modeling with Scale and Spatial Markovian Conditioning","created":"2025-05-19","cited_by_count":8,"area":null},{"id":"2405.13335","title":"Vision Transformer with Sparse Scan Prior","created":"2024-05-22","cited_by_count":6,"area":null},{"id":"2408.10527","title":"EdgeNAT: Transformer for Efficient Edge Detection","created":"2024-08-20","cited_by_count":6,"area":null},{"id":"2511.18452","title":"NAF: Zero-Shot Feature Upsampling via Neighborhood Attention Filtering","created":"2025-11-23","cited_by_count":6,"area":null},{"id":"2303.11860","title":"Online Transformers with Spiking Neurons for Fast Prosthetic Hand Control","created":"2023-03-21","cited_by_count":5,"area":null},{"id":"2304.00221","title":"Automatic High Resolution Wire Segmentation and Removal","created":"2023-04-01","cited_by_count":4,"area":null},{"id":"2403.00206","title":"MaskLRF: Self-supervised Pretraining via Masked Autoencoding of Local Reference Frames for Rotation-invariant 3D Point Set Analysis","created":"2024-03-01","cited_by_count":4,"area":null},{"id":"2511.00833","title":"Linear Differential Vision Transformer: Learning Visual Contrasts via Pairwise Differentials","created":"2025-11-02","cited_by_count":4,"area":null},{"id":"2406.19391","title":"Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across Heads","created":"2024-06-27","cited_by_count":3,"area":null},{"id":"2505.19795","title":"The Missing Point in Vision Transformers for Universal Image Segmentation","created":"2025-05-26","cited_by_count":3,"area":null},{"id":"2508.20987","title":"Webly-Supervised Image Manipulation Localization via Category-Aware Auto-Annotation","created":"2025-08-28","cited_by_count":3,"area":null},{"id":"2512.18363","title":"Enhancing 3D Semantic Scene Completion with a Refinement Module","created":"2025-12-20","cited_by_count":3,"area":null},{"id":"2603.25398","title":"PMT: Plain Mask Transformer for Image and Video Segmentation with Frozen Vision Encoders","created":"2026-03-26","cited_by_count":3,"area":null},{"id":"2305.05651","title":"SwinIA: Self-Supervised Blind-Spot Image Denoising without Convolutions","created":"2023-05-09","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":"2406.08859","title":"Fusion of regional and sparse attention in Vision Transformers","created":"2024-06-13","cited_by_count":2,"area":null},{"id":"2407.11546","title":"ParCon: Noise-Robust Collaborative Perception via Multi-module Parallel Connection","created":"2024-07-16","cited_by_count":2,"area":null},{"id":"2410.08226","title":"EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes","created":"2024-09-27","cited_by_count":2,"area":null},{"id":"2507.17892","title":"DiNAT-IR: Exploring Dilated Neighborhood Attention for High-Quality Image Restoration","created":"2025-07-23","cited_by_count":2,"area":null},{"id":"2605.31577","title":"SurGe: Improved Surface Geometry in Point Maps","created":"2026-05-29","cited_by_count":2,"area":null},{"id":"2411.18944","title":"Waterfall Transformer for Multi-person Pose Estimation","created":"2024-11-28","cited_by_count":1,"area":null},{"id":"2507.13546","title":"NABLA: Neighborhood Adaptive Block-Level Attention","created":"2025-07-17","cited_by_count":1,"area":null},{"id":"2601.06147","title":"LLM Flow Processes for Text-Conditioned Regression","created":"2026-01-05","cited_by_count":1,"area":null},{"id":"2601.21291","title":"Gaussian Belief Propagation Network for Depth Completion","created":"2026-01-29","cited_by_count":1,"area":null},{"id":"2602.21010","title":"Le-DETR: Revisiting Real-Time Detection Transformer with Efficient Encoder Design","created":"2026-02-24","cited_by_count":1,"area":null},{"id":"2211.06083","title":"Token Transformer: Can class token help window-based transformer build better long-range interactions?","created":"2022-11-11","cited_by_count":0,"area":null},{"id":"2312.08853","title":"Guided Image Restoration via Simultaneous Feature and Image Guided Fusion","created":"2023-12-14","cited_by_count":0,"area":null},{"id":"2404.00069","title":"A Two-Phase Recall-and-Select Framework for Fast Model Selection","created":"2024-03-28","cited_by_count":0,"area":null},{"id":"2407.07603","title":"iiANET: Inception Inspired Attention Hybrid Network for efficient Long-Range Dependency","created":"2024-07-10","cited_by_count":0,"area":null},{"id":"2502.13637","title":"Exploring Mutual Cross-Modal Attention for Context-Aware Human Affordance Generation","created":"2025-02-19","cited_by_count":0,"area":null},{"id":"2506.07414","title":"DPFormer: Dynamic Prompt Transformer for Continual Learning","created":"2025-06-09","cited_by_count":0,"area":null},{"id":"2507.05849","title":"DFYP: A Dynamic Fusion Framework with Spectral Channel Attention and Adaptive Operator learning for Crop Yield Prediction","created":"2025-07-08","cited_by_count":0,"area":null},{"id":"2508.19742","title":"Adaptive Dual-Constrained Line Aggregation for Cross-Paradigm Line Segment Detection","created":"2025-08-27","cited_by_count":0,"area":null},{"id":"2601.06443","title":"How to Build Robust, Scalable Models for GSV-Based Indicators in Neighborhood Research","created":"2026-01-10","cited_by_count":0,"area":null},{"id":"2607.10214","title":"ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation","created":"2026-07-11","cited_by_count":0,"area":null}],"next_cursor":null}