{"list":"other","total":51,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"1409.0575","title":"ImageNet Large Scale Visual Recognition Challenge","created":"2014-09-01","cited_by_count":8498},{"id":"2303.05499","title":"Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection","created":"2023-03-09","cited_by_count":3332},{"id":"2001.07685","title":"FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence","created":"2020-01-21","cited_by_count":2085},{"id":"2103.13413","title":"Vision Transformers for Dense Prediction","created":"2021-03-24","cited_by_count":1803},{"id":"1907.01341","title":"Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer","created":"2019-07-02","cited_by_count":1495},{"id":"1709.06158","title":"Matterport3D: Learning from RGB-D Data in Indoor Environments","created":"2017-09-18","cited_by_count":1376},{"id":"2401.10891","title":"Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data","created":"2024-01-19","cited_by_count":1360},{"id":"1506.03365","title":"LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop","created":"2015-06-10","cited_by_count":1355},{"id":"1911.04252","title":"Self-training with Noisy Student improves ImageNet classification","created":"2019-11-11","cited_by_count":1311},{"id":"1805.04687","title":"BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning","created":"2018-05-12","cited_by_count":1288},{"id":"1704.07813","title":"Unsupervised Learning of Depth and Ego-Motion from Video","created":"2017-04-25","cited_by_count":782},{"id":"1804.00607","title":"MegaDepth: Learning Single-View Depth Prediction from Internet Photos","created":"2018-04-02","cited_by_count":737},{"id":"2302.12288","title":"ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth","created":"2023-02-23","cited_by_count":657},{"id":"2003.14338","title":"TartanAir: A Dataset to Push the Limits of Visual SLAM","created":"2020-03-31","cited_by_count":506},{"id":"1911.10127","title":"BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks","created":"2019-11-22","cited_by_count":490},{"id":"1702.01105","title":"Joint 2D-3D-Semantic Data for Indoor Scene Understanding","created":"2017-02-03","cited_by_count":406},{"id":"2307.10984","title":"Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image","created":"2023-07-20","cited_by_count":365},{"id":"2006.06882","title":"Rethinking Pre-training and Self-training","created":"2020-06-11","cited_by_count":352},{"id":"2312.02145","title":"Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation","created":"2023-12-04","cited_by_count":327},{"id":"2004.01804","title":"Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval","created":"2020-04-03","cited_by_count":309},{"id":"1908.00222","title":"Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling","created":"2019-08-01","cited_by_count":286},{"id":"1604.03901","title":"Single-Image Depth Perception in the Wild","created":"2016-04-13","cited_by_count":180},{"id":"2307.14460","title":"MiDaS v3.1 -- A Model Zoo for Robust Monocular Relative Depth Estimation","created":"2023-07-26","cited_by_count":174},{"id":"2011.11498","title":"HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features","created":"2020-11-23","cited_by_count":105},{"id":"2306.17253","title":"Towards Zero-Shot Scale-Aware Monocular Depth Estimation","created":"2023-06-29","cited_by_count":101},{"id":"1807.09620","title":"OmniDepth: Dense Depth Estimation for Indoors Spherical Panoramas","created":"2018-07-25","cited_by_count":99},{"id":"2203.09283","title":"PanoFormer: Panorama Transformer for Indoor 360 Depth Estimation","created":"2022-03-17","cited_by_count":95},{"id":"1809.02587","title":"Self-Supervised Generation of Spatial Audio for 360 Video","created":"2018-09-07","cited_by_count":93},{"id":"2102.03550","title":"UniFuse: Unidirectional Fusion for 360$^{\\circ}$ Panorama Depth Estimation","created":"2021-02-06","cited_by_count":92},{"id":"1806.01320","title":"Cube Padding for Weakly-Supervised Saliency Prediction in 360{\\deg} Videos","created":"2018-06-04","cited_by_count":66},{"id":"2203.00838","title":"OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusion","created":"2022-03-02","cited_by_count":61},{"id":"2111.15669","title":"360MonoDepth: High-Resolution 360{\\deg} Monocular Depth Estimation","created":"2021-11-30","cited_by_count":60},{"id":"1812.03115","title":"Kernel Transformer Networks for Compact Spherical Convolution","created":"2018-12-07","cited_by_count":56},{"id":"1909.08112","title":"Spherical View Synthesis for Self-Supervised 360 Depth Estimation","created":"2019-09-17","cited_by_count":51},{"id":"2110.11590","title":"DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes","created":"2021-10-22","cited_by_count":46},{"id":"2304.07803","title":"EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation","created":"2023-04-16","cited_by_count":43},{"id":"1811.05304","title":"Self-Supervised Learning of Depth and Camera Motion from 360{\\deg} Videos","created":"2018-11-13","cited_by_count":40},{"id":"1911.04460","title":"360SD-Net: 360{\\deg} Stereo Depth Estimation with Learnable Cost Volume","created":"2019-11-11","cited_by_count":40},{"id":"2112.14440","title":"ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth Estimation","created":"2021-12-29","cited_by_count":39},{"id":"2303.11616","title":"HRDFuse: Monocular 360{\\deg}Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions","created":"2023-03-21","cited_by_count":37},{"id":"2209.02952","title":"BiFuse++: Self-supervised and Efficient Bi-projection Fusion for 360 Depth Estimation","created":"2022-09-07","cited_by_count":35},{"id":"1908.08344","title":"Indoor Depth Completion with Boundary Consistency and Self-Attention","created":"2019-08-22","cited_by_count":29},{"id":"2108.10843","title":"Bridging Unsupervised and Supervised Depth from Focus via All-in-Focus Supervision","created":"2021-08-24","cited_by_count":23},{"id":"2203.09855","title":"Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion","created":"2022-03-18","cited_by_count":23},{"id":"2202.02796","title":"GLPanoDepth: Global-to-Local Panoramic Depth Estimation","created":"2022-02-06","cited_by_count":16},{"id":"2202.08010","title":"360 Depth Estimation in the Wild -- The Depth360 Dataset and the SegFuse Network","created":"2022-02-16","cited_by_count":15},{"id":"2106.14166","title":"Indoor Panorama Planar 3D Reconstruction via Divide and Conquer","created":"2021-06-27","cited_by_count":9},{"id":"2401.13786","title":"FoVA-Depth: Field-of-View Agnostic Depth Estimation for Cross-Dataset Generalization","created":"2024-01-24","cited_by_count":8},{"id":"2204.05007","title":"HiMODE: A Hybrid Monocular Omnidirectional Depth Estimation Model","created":"2022-04-11","cited_by_count":6},{"id":"2401.10560","title":"360ORB-SLAM: A Visual SLAM System for Panoramic Images with Depth Completion Network","created":"2024-01-19","cited_by_count":5}],"next_cursor":null}