{"total":13,"rows":[{"id":"2206.05253","title":"Rethinking Spatial Invariance of Convolutional Networks for Object Counting","created":"2022-06-10","cited_by_count":54,"area":null},{"id":"2212.02573","title":"Domain-General Crowd Counting in Unseen Scenarios","created":"2022-12-05","cited_by_count":20,"area":null},{"id":"2208.02894","title":"Redesigning Multi-Scale Neural Network for Crowd Counting","created":"2022-08-04","cited_by_count":17,"area":null},{"id":"2312.01711","title":"Regressor-Segmenter Mutual Prompt Learning for Crowd Counting","created":"2023-12-04","cited_by_count":16,"area":null},{"id":"2112.15509","title":"Scene-Adaptive Attention Network for Crowd Counting","created":"2021-12-31","cited_by_count":12,"area":null},{"id":"2304.11677","title":"RGB-D Indiscernible Object Counting in Underwater Scenes","created":"2023-04-23","cited_by_count":9,"area":null},{"id":"2307.08536","title":"Variational Probabilistic Fusion Network for RGB-T Semantic Segmentation","created":"2023-07-17","cited_by_count":7,"area":null},{"id":"2404.07847","title":"The Effectiveness of a Simplified Model Structure for Crowd Counting","created":"2024-04-11","cited_by_count":3,"area":null},{"id":"2203.04061","title":"Counting with Adaptive Auxiliary Learning","created":"2022-03-08","cited_by_count":1,"area":null},{"id":"2204.07406","title":"SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing","created":"2022-04-15","cited_by_count":1,"area":null},{"id":"2304.05255","title":"Density Map Distillation for Incremental Object Counting","created":"2023-04-11","cited_by_count":1,"area":null},{"id":"2402.03758","title":"Virtual Classification: Modulating Domain-Specific Knowledge for Multidomain Crowd Counting","created":"2024-02-06","cited_by_count":1,"area":null},{"id":"2206.05648","title":"Indirect-Instant Attention Optimization for Crowd Counting in Dense Scenes","created":"2022-06-12","cited_by_count":0,"area":null}],"next_cursor":null}