{"list":"other","total":56,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1807.06521","title":"CBAM: Convolutional Block Attention Module","created":"2018-07-17","cited_by_count":2477},{"id":"1606.04797","title":"V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation","created":"2016-06-15","cited_by_count":2292},{"id":"2006.10739","title":"Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains","created":"2020-06-18","cited_by_count":2200},{"id":"2103.13415","title":"Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields","created":"2021-03-24","cited_by_count":1964},{"id":"1502.03044","title":"Show, Attend and Tell: Neural Image Caption Generation with Visual Attention","created":"2015-02-10","cited_by_count":1423},{"id":"1712.07629","title":"SuperPoint: Self-Supervised Interest Point Detection and Description","created":"2017-12-20","cited_by_count":1320},{"id":"1603.06937","title":"Stacked Hourglass Networks for Human Pose Estimation","created":"2016-03-22","cited_by_count":915},{"id":"1808.01244","title":"CornerNet: Detecting Objects as Paired Keypoints","created":"2018-08-03","cited_by_count":763},{"id":"1904.08189","title":"CenterNet: Keypoint Triplets for Object Detection","created":"2019-04-17","cited_by_count":654},{"id":"1504.06375","title":"Holistically-Nested Edge Detection","created":"2015-04-24","cited_by_count":592},{"id":"1802.05384","title":"AtlasNet: A Papier-M\\^ach\\'e Approach to Learning 3D Surface Generation","created":"2018-02-15","cited_by_count":539},{"id":"1804.06208","title":"Simple Baselines for Human Pose Estimation and Tracking","created":"2018-04-17","cited_by_count":502},{"id":"1901.06523","title":"Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks","created":"2019-01-19","cited_by_count":368},{"id":"2109.08141","title":"An End-to-End Transformer Model for 3D Object Detection","created":"2021-09-16","cited_by_count":329},{"id":"1605.09673","title":"Dynamic Filter Networks","created":"2016-05-31","cited_by_count":319},{"id":"2105.09492","title":"DeepCAD: A Deep Generative Network for Computer-Aided Design Models","created":"2021-05-20","cited_by_count":271},{"id":"2002.10880","title":"PolyGen: An Autoregressive Generative Model of 3D Meshes","created":"2020-02-23","cited_by_count":269},{"id":"1705.01389","title":"Learning to Estimate 3D Hand Pose from Single RGB Images","created":"2017-05-03","cited_by_count":234},{"id":"2012.12821","title":"Focal Frequency Loss for Image Reconstruction and Synthesis","created":"2020-12-23","cited_by_count":206},{"id":"2002.12416","title":"Learning in the Frequency Domain","created":"2020-02-27","cited_by_count":198},{"id":"1807.01232","title":"SpaceNet: A Remote Sensing Dataset and Challenge Series","created":"2018-07-03","cited_by_count":179},{"id":"2012.11879","title":"FcaNet: Frequency Channel Attention Networks","created":"2020-12-22","cited_by_count":179},{"id":"1511.03339","title":"Attention to Scale: Scale-aware Semantic Image Segmentation","created":"2015-11-10","cited_by_count":169},{"id":"2103.02370","title":"FSDR: Frequency Space Domain Randomization for Domain Generalization","created":"2021-03-03","cited_by_count":164},{"id":"1612.02103","title":"Richer Convolutional Features for Edge Detection","created":"2016-12-07","cited_by_count":143},{"id":"2003.04560","title":"Frequency Bias in Neural Networks for Input of Non-Uniform Density","created":"2020-03-10","cited_by_count":140},{"id":"1911.06465","title":"Fourier Spectrum Discrepancies in Deep Network Generated Images","created":"2019-11-15","cited_by_count":139},{"id":"1803.08999","title":"LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image","created":"2018-03-23","cited_by_count":95},{"id":"1807.10097","title":"Learning to predict crisp boundaries","created":"2018-07-26","cited_by_count":82},{"id":"2101.01909","title":"Line Segment Detection Using Transformers without Edges","created":"2021-01-06","cited_by_count":73},{"id":"1902.10903","title":"Bi-Directional Cascade Network for Perceptual Edge Detection","created":"2019-02-28","cited_by_count":72},{"id":"1905.03246","title":"End-to-End Wireframe Parsing","created":"2019-05-08","cited_by_count":72},{"id":"2007.07527","title":"Learning to Parse Wireframes in Images of Man-Made Environments","created":"2020-07-15","cited_by_count":71},{"id":"2003.01663","title":"Holistically-Attracted Wireframe Parsing","created":"2020-03-03","cited_by_count":64},{"id":"1812.02122","title":"Learning Attraction Field Representation for Robust Line Segment Detection","created":"2018-12-05","cited_by_count":52},{"id":"1412.1123","title":"DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection","created":"2014-12-02","cited_by_count":50},{"id":"2106.02874","title":"RDA: Robust Domain Adaptation via Fourier Adversarial Attacking","created":"2021-06-05","cited_by_count":48},{"id":"2007.09493","title":"Deep Hough-Transform Line Priors","created":"2020-07-18","cited_by_count":44},{"id":"1903.01700","title":"EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection","created":"2019-03-05","cited_by_count":39},{"id":"1905.03415","title":"PPGNet: Learning Point-Pair Graph for Line Segment Detection","created":"2019-05-09","cited_by_count":39},{"id":"1703.06241","title":"RoomNet: End-to-End Room Layout Estimation","created":"2017-03-18","cited_by_count":38},{"id":"1511.07386","title":"Pushing the Boundaries of Boundary Detection using Deep Learning","created":"2015-11-23","cited_by_count":35},{"id":"1603.04530","title":"Object Contour Detection with a Fully Convolutional Encoder-Decoder Network","created":"2016-03-15","cited_by_count":34},{"id":"2011.09808","title":"Unmixing Convolutional Features for Crisp Edge Detection","created":"2020-11-19","cited_by_count":32},{"id":"2111.15143","title":"HEAT: Holistic Edge Attention Transformer for Structured Reconstruction","created":"2021-11-30","cited_by_count":29},{"id":"1908.11025","title":"Deep Floor Plan Recognition Using a Multi-Task Network with Room-Boundary-Guided Attention","created":"2019-08-29","cited_by_count":27},{"id":"2103.11161","title":"MonteFloor: Extending MCTS for Reconstructing Accurate Large-Scale Floor Plans","created":"2021-03-20","cited_by_count":26},{"id":"1412.4181","title":"Oriented Edge Forests for Boundary Detection","created":"2014-12-13","cited_by_count":25},{"id":"1506.04449","title":"Compressing Convolutional Neural Networks","created":"2015-06-14","cited_by_count":25},{"id":"1912.01756","title":"Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction","created":"2019-12-04","cited_by_count":25},{"id":"1902.09104","title":"Dynamic Feature Fusion for Semantic Edge Detection","created":"2019-02-25","cited_by_count":16},{"id":"1801.02439","title":"Deep Crisp Boundaries: From Boundaries to Higher-level Tasks","created":"2018-01-08","cited_by_count":15},{"id":"1912.05135","title":"Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference","created":"2019-12-11","cited_by_count":12},{"id":"2108.07990","title":"Structured Outdoor Architecture Reconstruction by Exploration and Classification","created":"2021-08-18","cited_by_count":6}],"next_cursor":null}