{"list":"other","total":52,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2304.02643","title":"Segment Anything","created":"2023-04-05","cited_by_count":8234},{"id":"1903.11027","title":"nuScenes: A multimodal dataset for autonomous driving","created":"2019-03-26","cited_by_count":4523},{"id":"1807.02758","title":"Image Super-Resolution Using Very Deep Residual Channel Attention Networks","created":"2018-07-08","cited_by_count":1264},{"id":"2306.14289","title":"Faster Segment Anything: Towards Lightweight SAM for Mobile Applications","created":"2023-06-25","cited_by_count":352},{"id":"2006.04139","title":"Learning Texture Transformer Network for Image Super-Resolution","created":"2020-06-07","cited_by_count":347},{"id":"2110.04994","title":"Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans","created":"2021-10-11","cited_by_count":336},{"id":"2007.10042","title":"Non-Local Spatial Propagation Network for Depth Completion","created":"2020-07-20","cited_by_count":195},{"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":"1810.02695","title":"Learning Depth with Convolutional Spatial Propagation Network","created":"2018-10-04","cited_by_count":136},{"id":"1812.00488","title":"DeepLiDAR: Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image","created":"2018-12-02","cited_by_count":129},{"id":"1904.05373","title":"Pixel-Adaptive Convolutional Neural Networks","created":"2019-04-10","cited_by_count":126},{"id":"1908.01238","title":"Learning Guided Convolutional Network for Depth Completion","created":"2019-08-03","cited_by_count":111},{"id":"1910.06727","title":"Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints","created":"2019-10-15","cited_by_count":108},{"id":"2008.00418","title":"Blind Face Restoration via Deep Multi-scale Component Dictionaries","created":"2020-08-02","cited_by_count":106},{"id":"2211.13202","title":"Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation","created":"2022-11-23","cited_by_count":100},{"id":"2304.13030","title":"CompletionFormer: Depth Completion with Convolutions and Vision Transformers","created":"2023-04-25","cited_by_count":93},{"id":"1807.11699","title":"SegStereo: Exploiting Semantic Information for Disparity Estimation","created":"2018-07-31","cited_by_count":88},{"id":"2106.02299","title":"MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution","created":"2021-06-04","cited_by_count":80},{"id":"2107.13802","title":"RigNet: Repetitive Image Guided Network for Depth Completion","created":"2021-07-29","cited_by_count":80},{"id":"1902.05356","title":"Sparse and noisy LiDAR completion with RGB guidance and uncertainty","created":"2019-02-14","cited_by_count":79},{"id":"1910.04066","title":"Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion","created":"2019-10-09","cited_by_count":79},{"id":"2104.06977","title":"Discrete Cosine Transform Network for Guided Depth Map Super-Resolution","created":"2021-04-14","cited_by_count":71},{"id":"2008.11351","title":"SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentation for Accurate Freespace Detection","created":"2020-08-26","cited_by_count":66},{"id":"2104.06174","title":"Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline","created":"2021-04-13","cited_by_count":61},{"id":"1910.08373","title":"Deformable Kernel Networks for Joint Image Filtering","created":"2019-10-17","cited_by_count":59},{"id":"2304.07039","title":"Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancement","created":"2023-04-14","cited_by_count":57},{"id":"2108.08829","title":"Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation","created":"2021-08-19","cited_by_count":55},{"id":"1712.09809","title":"A Multi-Scale and Multi-Depth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening","created":"2017-12-28","cited_by_count":54},{"id":"2104.14107","title":"Decoupled Dynamic Filter Networks","created":"2021-04-29","cited_by_count":53},{"id":"1710.04200","title":"Joint Image Filtering with Deep Convolutional Networks","created":"2017-10-11","cited_by_count":52},{"id":"2211.11592","title":"Guided Depth Super-Resolution by Deep Anisotropic Diffusion","created":"2022-11-21","cited_by_count":46},{"id":"2103.04584","title":"Deep Gradient Projection Networks for Pan-sharpening","created":"2021-03-08","cited_by_count":44},{"id":"2006.01469","title":"Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution","created":"2020-06-02","cited_by_count":40},{"id":"2107.12541","title":"BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation","created":"2021-07-27","cited_by_count":31},{"id":"2103.12955","title":"Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution","created":"2021-03-24","cited_by_count":30},{"id":"2303.08942","title":"Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution","created":"2023-03-15","cited_by_count":28},{"id":"2203.14297","title":"Learning Graph Regularisation for Guided Super-Resolution","created":"2022-03-27","cited_by_count":27},{"id":"2211.10994","title":"DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion","created":"2022-11-20","cited_by_count":27},{"id":"2312.05799","title":"SGNet: Structure Guided Network via Gradient-Frequency Awareness for Depth Map Super-Resolution","created":"2023-12-10","cited_by_count":27},{"id":"2203.04960","title":"Memory-augmented Deep Unfolding Network for Guided Image Super-resolution","created":"2022-02-12","cited_by_count":25},{"id":"2207.08689","title":"Quality Assessment of Image Super-Resolution: Balancing Deterministic and Statistical Fidelity","created":"2022-07-15","cited_by_count":24},{"id":"2104.01530","title":"High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion","created":"2021-04-04","cited_by_count":20},{"id":"2306.00386","title":"Symmetric Uncertainty-Aware Feature Transmission for Depth Super-Resolution","created":"2023-06-01","cited_by_count":19},{"id":"2112.06401","title":"Deep Attentional Guided Image Filtering","created":"2021-12-13","cited_by_count":17},{"id":"2301.13419","title":"Recurrent Structure Attention Guidance for Depth Super-Resolution","created":"2023-01-31","cited_by_count":16},{"id":"2305.07774","title":"PanFlowNet: A Flow-Based Deep Network for Pan-sharpening","created":"2023-05-12","cited_by_count":16},{"id":"2004.06163","title":"Blind Quality Assessment for Image Superresolution Using Deep Two-Stream Convolutional Networks","created":"2020-04-13","cited_by_count":15},{"id":"2301.13416","title":"Structure Flow-Guided Network for Real Depth Super-Resolution","created":"2023-01-31","cited_by_count":14},{"id":"2207.09156","title":"Learning Mutual Modulation for Self-Supervised Cross-Modal Super-Resolution","created":"2022-07-19","cited_by_count":11},{"id":"2311.07166","title":"NDDepth: Normal-Distance Assisted Monocular Depth Estimation and Completion","created":"2023-11-13","cited_by_count":9},{"id":"2212.09581","title":"Reference-based Image and Video Super-Resolution via C2-Matching","created":"2022-12-19","cited_by_count":8}],"next_cursor":null}