{"list":"other","total":116,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"2201.05989","title":"Instant Neural Graphics Primitives with a Multiresolution Hash Encoding","created":"2022-01-16","cited_by_count":3723},{"id":"1912.04958","title":"Analyzing and Improving the Image Quality of StyleGAN","created":"2019-12-03","cited_by_count":3588},{"id":"1710.10196","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","created":"2017-10-27","cited_by_count":2988},{"id":"1512.03012","title":"ShapeNet: An Information-Rich 3D Model Repository","created":"2015-12-09","cited_by_count":2897},{"id":"1901.05103","title":"DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation","created":"2019-01-16","cited_by_count":2689},{"id":"1809.11096","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","created":"2018-09-28","cited_by_count":2626},{"id":"2006.09661","title":"Implicit Neural Representations with Periodic Activation Functions","created":"2020-06-17","cited_by_count":2238},{"id":"1812.03828","title":"Occupancy Networks: Learning 3D Reconstruction in Function Space","created":"2018-12-10","cited_by_count":2041},{"id":"2106.10689","title":"NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction","created":"2021-06-20","cited_by_count":1712},{"id":"2012.02190","title":"pixelNeRF: Neural Radiance Fields from One or Few Images","created":"2020-12-03","cited_by_count":1584},{"id":"2008.02268","title":"NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections","created":"2020-08-05","cited_by_count":1232},{"id":"2112.07945","title":"Efficient Geometry-aware 3D Generative Adversarial Networks","created":"2021-12-15","cited_by_count":1205},{"id":"2106.12423","title":"Alias-Free Generative Adversarial Networks","created":"2021-06-23","cited_by_count":1184},{"id":"1912.01865","title":"StarGAN v2: Diverse Image Synthesis for Multiple Domains","created":"2019-12-04","cited_by_count":1098},{"id":"1812.02822","title":"Learning Implicit Fields for Generative Shape Modeling","created":"2018-12-06","cited_by_count":1060},{"id":"1711.09020","title":"StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation","created":"2017-11-24","cited_by_count":1039},{"id":"2007.11571","title":"Neural Sparse Voxel Fields","created":"2020-07-22","cited_by_count":959},{"id":"2103.14024","title":"PlenOctrees for Real-time Rendering of Neural Radiance Fields","created":"2021-03-25","cited_by_count":905},{"id":"2010.07492","title":"NeRF++: Analyzing and Improving Neural Radiance Fields","created":"2020-10-15","cited_by_count":861},{"id":"1905.05172","title":"PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization","created":"2019-05-13","cited_by_count":818},{"id":"2011.12100","title":"GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields","created":"2020-11-24","cited_by_count":785},{"id":"2003.04618","title":"Convolutional Occupancy Networks","created":"2020-03-10","cited_by_count":761},{"id":"2002.10099","title":"Implicit Geometric Regularization for Learning Shapes","created":"2020-02-24","cited_by_count":710},{"id":"2012.00926","title":"pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis","created":"2020-12-02","cited_by_count":708},{"id":"2102.13090","title":"IBRNet: Learning Multi-View Image-Based Rendering","created":"2021-02-25","cited_by_count":703},{"id":"1912.07372","title":"Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision","created":"2019-12-16","cited_by_count":700},{"id":"2007.02442","title":"GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis","created":"2020-07-05","cited_by_count":689},{"id":"2103.13744","title":"KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs","created":"2021-03-25","cited_by_count":673},{"id":"2109.00512","title":"Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction","created":"2021-09-01","cited_by_count":652},{"id":"2104.10078","title":"UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction","created":"2021-04-20","cited_by_count":646},{"id":"2111.11426","title":"Neural Fields in Visual Computing and Beyond","created":"2021-11-22","cited_by_count":540},{"id":"2004.00452","title":"PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization","created":"2020-04-01","cited_by_count":521},{"id":"2103.10380","title":"FastNeRF: High-Fidelity Neural Rendering at 200FPS","created":"2021-03-18","cited_by_count":511},{"id":"2012.03927","title":"NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis","created":"2020-12-07","cited_by_count":496},{"id":"2110.08985","title":"StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis","created":"2021-10-18","cited_by_count":477},{"id":"2012.03918","title":"NeRD: Neural Reflectance Decomposition from Image Collections","created":"2020-12-07","cited_by_count":449},{"id":"2209.11163","title":"GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images","created":"2022-09-22","cited_by_count":446},{"id":"2011.03277","title":"Modular Primitives for High-Performance Differentiable Rendering","created":"2020-11-06","cited_by_count":441},{"id":"1911.10414","title":"SAL: Sign Agnostic Learning of Shapes from Raw Data","created":"2019-11-23","cited_by_count":390},{"id":"2003.08981","title":"Local Implicit Grid Representations for 3D Scenes","created":"2020-03-19","cited_by_count":373},{"id":"2111.05849","title":"Advances in Neural Rendering","created":"2021-11-10","cited_by_count":365},{"id":"2003.01456","title":"Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion","created":"2020-03-03","cited_by_count":343},{"id":"1905.10711","title":"DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction","created":"2019-05-26","cited_by_count":333},{"id":"1606.02147","title":"ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation","created":"2016-06-07","cited_by_count":291},{"id":"2110.13903","title":"NeRV: Neural Representations for Videos","created":"2021-10-26","cited_by_count":256},{"id":"1904.06447","title":"Learning Shape Templates with Structured Implicit Functions","created":"2019-04-12","cited_by_count":242},{"id":"2012.02189","title":"Learned Initializations for Optimizing Coordinate-Based Neural Representations","created":"2020-12-03","cited_by_count":242},{"id":"2109.01847","title":"Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering","created":"2021-09-04","cited_by_count":228},{"id":"2105.06466","title":"Editing Conditional Radiance Fields","created":"2021-05-13","cited_by_count":222},{"id":"2205.04978","title":"NeRF-Editing: Geometry Editing of Neural Radiance Fields","created":"2022-05-10","cited_by_count":217},{"id":"2012.01714","title":"AutoInt: Automatic Integration for Fast Neural Volume Rendering","created":"2020-12-03","cited_by_count":204},{"id":"2008.03824","title":"Neural Reflectance Fields for Appearance Acquisition","created":"2020-08-09","cited_by_count":196},{"id":"2010.04595","title":"GRF: Learning a General Radiance Field for 3D Representation and Rendering","created":"2020-10-09","cited_by_count":183},{"id":"2109.01750","title":"CodeNeRF: Disentangled Neural Radiance Fields for Object Categories","created":"2021-09-03","cited_by_count":183},{"id":"1612.00404","title":"Learning Shape Abstractions by Assembling Volumetric Primitives","created":"2016-12-01","cited_by_count":181},{"id":"1909.05736","title":"CvxNet: Learnable Convex Decomposition","created":"2019-09-12","cited_by_count":174},{"id":"1811.11606","title":"Escaping Plato's Cave: 3D Shape From Adversarial Rendering","created":"2018-11-28","cited_by_count":170},{"id":"1707.00683","title":"Modulating early visual processing by language","created":"2017-07-02","cited_by_count":167},{"id":"2002.08988","title":"BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images","created":"2020-02-20","cited_by_count":166},{"id":"2011.12490","title":"DeRF: Decomposed Radiance Fields","created":"2020-11-25","cited_by_count":163},{"id":"1707.05776","title":"Optimizing the Latent Space of Generative Networks","created":"2017-07-18","cited_by_count":157},{"id":"2103.15606","title":"GNeRF: GAN-based Neural Radiance Field without Posed Camera","created":"2021-03-29","cited_by_count":153},{"id":"2110.09788","title":"CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis","created":"2021-10-19","cited_by_count":149},{"id":"2207.11911","title":"NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editing","created":"2022-07-25","cited_by_count":142},{"id":"2104.00670","title":"Unconstrained Scene Generation with Locally Conditioned Radiance Fields","created":"2021-04-01","cited_by_count":130},{"id":"1904.09970","title":"Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboids","created":"2019-04-22","cited_by_count":124},{"id":"1612.05872","title":"3D Shape Induction from 2D Views of Multiple Objects","created":"2016-12-18","cited_by_count":121},{"id":"1911.10949","title":"PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes","created":"2019-11-25","cited_by_count":119},{"id":"2011.13650","title":"Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence","created":"2020-11-27","cited_by_count":119},{"id":"1908.04520","title":"SDM-NET: Deep Generative Network for Structured Deformable Mesh","created":"2019-08-13","cited_by_count":113},{"id":"2006.03997","title":"MeshSDF: Differentiable Iso-Surface Extraction","created":"2020-06-06","cited_by_count":112},{"id":"2111.15490","title":"FENeRF: Face Editing in Neural Radiance Fields","created":"2021-11-30","cited_by_count":112},{"id":"1912.06395","title":"Neural Cages for Detail-Preserving 3D Deformations","created":"2019-12-13","cited_by_count":106},{"id":"1912.05237","title":"Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis","created":"2019-12-11","cited_by_count":104},{"id":"2103.10429","title":"Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks","created":"2021-03-18","cited_by_count":103},{"id":"2010.09125","title":"Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering","created":"2020-10-18","cited_by_count":101},{"id":"1908.04725","title":"Learning elementary structures for 3D shape generation and matching","created":"2019-08-13","cited_by_count":98},{"id":"2104.07659","title":"GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds","created":"2021-04-15","cited_by_count":98},{"id":"2003.12181","title":"ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds","created":"2020-03-26","cited_by_count":96},{"id":"1811.08988","title":"Supervised Fitting of Geometric Primitives to 3D Point Clouds","created":"2018-11-22","cited_by_count":91},{"id":"2203.14954","title":"GIRAFFE HD: A High-Resolution 3D-aware Generative Model","created":"2022-03-28","cited_by_count":86},{"id":"2011.01437","title":"Learning Deformable Tetrahedral Meshes for 3D Reconstruction","created":"2020-11-03","cited_by_count":85},{"id":"2004.02869","title":"DualSDF: Semantic Shape Manipulation using a Two-Level Representation","created":"2020-04-06","cited_by_count":82},{"id":"1708.01648","title":"3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks","created":"2017-08-04","cited_by_count":77},{"id":"1905.11911","title":"Controlling Neural Level Sets","created":"2019-05-28","cited_by_count":76},{"id":"2004.01176","title":"Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image","created":"2020-04-02","cited_by_count":72},{"id":"2103.16552","title":"Unsupervised Learning of 3D Object Categories from Videos in the Wild","created":"2021-03-30","cited_by_count":67},{"id":"2207.03434","title":"LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery","created":"2022-07-07","cited_by_count":66},{"id":"2112.01983","title":"CoNeRF: Controllable Neural Radiance Fields","created":"2021-12-03","cited_by_count":65},{"id":"1904.01326","title":"HoloGAN: Unsupervised learning of 3D representations from natural images","created":"2019-04-02","cited_by_count":59},{"id":"1908.00575","title":"StructureNet: Hierarchical Graph Networks for 3D Shape Generation","created":"2019-08-01","cited_by_count":59},{"id":"2204.10850","title":"Control-NeRF: Editable Feature Volumes for Scene Rendering and Manipulation","created":"2022-04-22","cited_by_count":57},{"id":"1804.05469","title":"Im2Struct: Recovering 3D Shape Structure from a Single RGB Image","created":"2018-04-16","cited_by_count":55},{"id":"2103.17269","title":"CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields","created":"2021-03-31","cited_by_count":55},{"id":"2003.09754","title":"Learning 3D Part Assembly from a Single Image","created":"2020-03-21","cited_by_count":52},{"id":"2112.11347","title":"Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects","created":"2021-12-21","cited_by_count":50}],"next_cursor":"100"}