{"total":18,"rows":[{"id":"2108.00941","title":"A Survey of Human-in-the-loop for Machine Learning","created":"2021-08-02","cited_by_count":215,"area":null},{"id":"2302.06378","title":"Semantic Image Segmentation: Two Decades of Research","created":"2023-02-13","cited_by_count":27,"area":null},{"id":"2101.01308","title":"CycleSegNet: Object Co-segmentation with Cycle Refinement and Region Correspondence","created":"2021-01-05","cited_by_count":19,"area":null},{"id":"2311.05770","title":"PolyMaX: General Dense Prediction with Mask Transformer","created":"2023-11-09","cited_by_count":14,"area":null},{"id":"2103.00259","title":"Exposing Semantic Segmentation Failures via Maximum Discrepancy Competition","created":"2021-02-27","cited_by_count":7,"area":null},{"id":"2110.15601","title":"Whole Brain Segmentation with Full Volume Neural Network","created":"2021-10-29","cited_by_count":5,"area":null},{"id":"2203.01087","title":"Vision-based Large-scale 3D Semantic Mapping for Autonomous Driving Applications","created":"2022-03-02","cited_by_count":4,"area":null},{"id":"2212.14215","title":"Local Learning on Transformers via Feature Reconstruction","created":"2022-12-29","cited_by_count":4,"area":null},{"id":"2103.05463","title":"Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentation","created":"2021-03-09","cited_by_count":2,"area":null},{"id":"2104.13824","title":"DeepSatData: Building large scale datasets of satellite images for training machine learning models","created":"2021-04-28","cited_by_count":2,"area":null},{"id":"2408.02039","title":"Pixel-Level Domain Adaptation: A New Perspective for Enhancing Weakly Supervised Semantic Segmentation","created":"2024-08-04","cited_by_count":2,"area":null},{"id":"2106.00566","title":"Full-Resolution Encoder-Decoder Networks with Multi-Scale Feature Fusion for Human Pose Estimation","created":"2021-06-01","cited_by_count":0,"area":null},{"id":"2108.09433","title":"BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation","created":"2021-08-21","cited_by_count":0,"area":null},{"id":"2109.10083","title":"PDFNet: Pointwise Dense Flow Network for Urban-Scene Segmentation","created":"2021-09-21","cited_by_count":0,"area":null},{"id":"2211.11242","title":"L-MAE: Masked Autoencoders are Semantic Segmentation Datasets Augmenter","created":"2022-11-21","cited_by_count":0,"area":null},{"id":"2211.15467","title":"Progressively Dual Prior Guided Few-shot Semantic Segmentation","created":"2022-11-20","cited_by_count":0,"area":null},{"id":"2310.15025","title":"P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic Segmentation","created":"2023-10-23","cited_by_count":0,"area":null},{"id":"2601.01167","title":"Cross-Layer Attentive Feature Upsampling for Low-latency Semantic Segmentation","created":"2026-01-03","cited_by_count":0,"area":null}],"next_cursor":null}