{"list":"other","total":105,"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":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"1405.0312","title":"Microsoft COCO: Common Objects in Context","created":"2014-05-01","cited_by_count":17608},{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"1703.06870","title":"Mask R-CNN","created":"2017-03-20","cited_by_count":7277},{"id":"1608.06993","title":"Densely Connected Convolutional Networks","created":"2016-08-25","cited_by_count":6720},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"id":"2203.00667","title":"Generative Adversarial Networks","created":"2022-03-01","cited_by_count":5627},{"id":"1411.4038","title":"Fully Convolutional Networks for Semantic Segmentation","created":"2014-11-14","cited_by_count":4859},{"id":"1801.04381","title":"MobileNetV2: Inverted Residuals and Linear Bottlenecks","created":"2018-01-13","cited_by_count":4795},{"id":"1606.00915","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","created":"2016-06-02","cited_by_count":3241},{"id":"1611.05431","title":"Aggregated Residual Transformations for Deep Neural Networks","created":"2016-11-16","cited_by_count":2546},{"id":"1612.01105","title":"Pyramid Scene Parsing Network","created":"2016-12-04","cited_by_count":2479},{"id":"1610.02357","title":"Xception: Deep Learning with Depthwise Separable Convolutions","created":"2016-10-07","cited_by_count":2332},{"id":"1705.07115","title":"Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics","created":"2017-05-19","cited_by_count":1358},{"id":"2210.09276","title":"Imagic: Text-Based Real Image Editing with Diffusion Models","created":"2022-10-17","cited_by_count":1178},{"id":"1611.04076","title":"Least Squares Generative Adversarial Networks","created":"2016-11-13","cited_by_count":1001},{"id":"1612.03716","title":"COCO-Stuff: Thing and Stuff Classes in Context","created":"2016-12-12","cited_by_count":864},{"id":"1804.02505","title":"MVSNet: Depth Inference for Unstructured Multi-view Stereo","created":"2018-04-07","cited_by_count":788},{"id":"2001.05566","title":"Image Segmentation Using Deep Learning: A Survey","created":"2020-01-15","cited_by_count":660},{"id":"1902.06162","title":"Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey","created":"2019-02-16","cited_by_count":657},{"id":"1711.06077","title":"The Perception-Distortion Tradeoff","created":"2017-11-16","cited_by_count":587},{"id":"1604.05144","title":"ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation","created":"2016-04-18","cited_by_count":331},{"id":"2106.03348","title":"ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias","created":"2021-06-07","cited_by_count":216},{"id":"1904.09569","title":"A Simple Pooling-Based Design for Real-Time Salient Object Detection","created":"2019-04-21","cited_by_count":212},{"id":"2102.10274","title":"Concealed Object Detection","created":"2021-02-20","cited_by_count":212},{"id":"1903.05854","title":"MirrorGAN: Learning Text-to-image Generation by Redescription","created":"2019-03-14","cited_by_count":176},{"id":"2012.07810","title":"Real-Time High-Resolution Background Matting","created":"2020-12-14","cited_by_count":173},{"id":"1703.07511","title":"Deep Photo Style Transfer","created":"2017-03-22","cited_by_count":168},{"id":"1904.09146","title":"Salient Object Detection in the Deep Learning Era: An In-Depth Survey","created":"2019-04-19","cited_by_count":164},{"id":"1803.10967","title":"Context-aware Synthesis for Video Frame Interpolation","created":"2018-03-29","cited_by_count":153},{"id":"1910.13049","title":"Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation","created":"2019-10-29","cited_by_count":151},{"id":"1703.03872","title":"Deep Image Matting","created":"2017-03-10","cited_by_count":150},{"id":"1904.05049","title":"Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution","created":"2019-04-10","cited_by_count":140},{"id":"2107.00910","title":"Learned Token Pruning for Transformers","created":"2021-07-02","cited_by_count":139},{"id":"1805.04096","title":"Fighting Fake News: Image Splice Detection via Learned Self-Consistency","created":"2018-05-10","cited_by_count":136},{"id":"1812.11941","title":"High Quality Monocular Depth Estimation via Transfer Learning","created":"2018-12-31","cited_by_count":133},{"id":"2011.11961","title":"MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition","created":"2020-11-24","cited_by_count":127},{"id":"2202.10108","title":"ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond","created":"2022-02-21","cited_by_count":117},{"id":"2011.08612","title":"Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things","created":"2020-11-17","cited_by_count":111},{"id":"2003.14023","title":"Learning Human-Object Interaction Detection using Interaction Points","created":"2020-03-31","cited_by_count":108},{"id":"2004.00626","title":"Background Matting: The World is Your Green Screen","created":"2020-04-01","cited_by_count":105},{"id":"1411.5878","title":"Salient Object Detection: A Survey","created":"2014-11-18","cited_by_count":98},{"id":"1908.00672","title":"Indices Matter: Learning to Index for Deep Image Matting","created":"2019-08-02","cited_by_count":93},{"id":"2010.16188","title":"Bridging Composite and Real: Towards End-to-end Deep Image Matting","created":"2020-10-30","cited_by_count":89},{"id":"2012.06722","title":"Mask Guided Matting via Progressive Refinement Network","created":"2020-12-12","cited_by_count":84},{"id":"1909.09725","title":"Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation","created":"2019-09-20","cited_by_count":79},{"id":"2001.04069","title":"Natural Image Matting via Guided Contextual Attention","created":"2020-01-13","cited_by_count":78},{"id":"1809.01354","title":"Semantic Human Matting","created":"2018-09-05","cited_by_count":67},{"id":"2106.14490","title":"Making Images Real Again: A Comprehensive Survey on Deep Image Composition","created":"2021-06-28","cited_by_count":63},{"id":"2104.14222","title":"Privacy-Preserving Portrait Matting","created":"2021-04-29","cited_by_count":60},{"id":"1707.05055","title":"Information-Flow Matting","created":"2017-07-17","cited_by_count":59},{"id":"2107.07235","title":"Deep Automatic Natural Image Matting","created":"2021-07-15","cited_by_count":59},{"id":"2104.08201","title":"Semantic Image Matting","created":"2021-04-16","cited_by_count":55},{"id":"1904.05475","title":"Learning to Generate Synthetic Data via Compositing","created":"2019-04-10","cited_by_count":52},{"id":"2009.07833","title":"Layered Neural Rendering for Retiming People in Video","created":"2020-09-16","cited_by_count":51},{"id":"1807.10088","title":"AlphaGAN: Generative adversarial networks for natural image matting","created":"2018-07-26","cited_by_count":50},{"id":"2003.07711","title":"$F$, $B$, Alpha Matting","created":"2020-03-17","cited_by_count":50},{"id":"2105.06993","title":"Omnimatte: Associating Objects and Their Effects in Video","created":"2021-05-14","cited_by_count":50},{"id":"2004.04955","title":"Boosting Semantic Human Matting with Coarse Annotations","created":"2020-04-10","cited_by_count":48},{"id":"2203.15662","title":"MatteFormer: Transformer-Based Image Matting via Prior-Tokens","created":"2022-03-29","cited_by_count":48},{"id":"1909.04686","title":"Disentangled Image Matting","created":"2019-09-10","cited_by_count":47},{"id":"2303.15105","title":"Vision Transformer with Quadrangle Attention","created":"2023-03-27","cited_by_count":46},{"id":"2107.09600","title":"DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation","created":"2021-07-20","cited_by_count":45},{"id":"1612.08510","title":"Learning Non-Lambertian Object Intrinsics across ShapeNet Categories","created":"2016-12-27","cited_by_count":42},{"id":"2104.11208","title":"Deep Video Matting via Spatio-Temporal Alignment and Aggregation","created":"2021-04-22","cited_by_count":41},{"id":"1907.06119","title":"Understanding Deep Learning Techniques for Image Segmentation","created":"2019-07-13","cited_by_count":38},{"id":"2004.01180","title":"Learning to See Through Obstructions","created":"2020-04-02","cited_by_count":38},{"id":"2011.14288","title":"Learning Affinity-Aware Upsampling for Deep Image Matting","created":"2020-11-29","cited_by_count":37},{"id":"2009.06613","title":"High-Resolution Deep Image Matting","created":"2020-09-14","cited_by_count":36},{"id":"1803.04636","title":"TOM-Net: Learning Transparent Object Matting from a Single Image","created":"2018-03-13","cited_by_count":34},{"id":"1602.06541","title":"A Survey of Semantic Segmentation","created":"2016-02-21","cited_by_count":30},{"id":"1707.08289","title":"Fast Deep Matting for Portrait Animation on Mobile Phone","created":"2017-07-26","cited_by_count":30},{"id":"2105.11427","title":"Attention-guided Temporally Coherent Video Object Matting","created":"2021-05-24","cited_by_count":25},{"id":"2203.16828","title":"Rethinking Portrait Matting with Privacy Preserving","created":"2022-03-31","cited_by_count":25},{"id":"2205.10767","title":"Human Instance Matting via Mutual Guidance and Multi-Instance Refinement","created":"2022-05-22","cited_by_count":25},{"id":"1805.11802","title":"CRRN: Multi-Scale Guided Concurrent Reflection Removal Network","created":"2018-05-30","cited_by_count":24},{"id":"2010.10056","title":"Real-time Localized Photorealistic Video Style Transfer","created":"2020-10-20","cited_by_count":24},{"id":"2012.08323","title":"Improved Image Matting via Real-time User Clicks and Uncertainty Estimation","created":"2020-12-15","cited_by_count":22},{"id":"2201.06889","title":"Boosting Robustness of Image Matting with Context Assembling and Strong Data Augmentation","created":"2022-01-18","cited_by_count":22},{"id":"2206.05149","title":"Referring Image Matting","created":"2022-06-10","cited_by_count":22},{"id":"2011.02146","title":"Deep Image Compositing","created":"2020-11-04","cited_by_count":21},{"id":"2008.05202","title":"Representative Graph Neural Network","created":"2020-08-12","cited_by_count":19},{"id":"2208.03007","title":"TransMatting: Enhancing Transparent Objects Matting with Transformers","created":"2022-08-05","cited_by_count":15},{"id":"2004.08096","title":"Fast Soft Color Segmentation","created":"2020-04-17","cited_by_count":13},{"id":"2109.12252","title":"Long-Range Feature Propagating for Natural Image Matting","created":"2021-09-25","cited_by_count":13},{"id":"2101.09095","title":"Towards Enhancing Fine-grained Details for Image Matting","created":"2021-01-22","cited_by_count":12},{"id":"2103.17062","title":"Smart Scribbles for Image Mating","created":"2021-03-31","cited_by_count":11},{"id":"2105.02646","title":"Cascade Image Matting with Deformable Graph Refinement","created":"2021-05-06","cited_by_count":11},{"id":"2101.02391","title":"Multi-scale Information Assembly for Image Matting","created":"2021-01-07","cited_by_count":10},{"id":"2110.12748","title":"Highly Efficient Natural Image Matting","created":"2021-10-25","cited_by_count":6},{"id":"1803.08435","title":"Guided Image Inpainting: Replacing an Image Region by Pulling Content from Another Image","created":"2018-03-22","cited_by_count":5},{"id":"2004.03249","title":"Hierarchical Opacity Propagation for Image Matting","created":"2020-04-07","cited_by_count":5},{"id":"2110.10898","title":"Deep Image Matting with Flexible Guidance Input","created":"2021-10-21","cited_by_count":5}],"next_cursor":"100"}