{"list":"other","total":63,"rows":[{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1606.08415","title":"Gaussian Error Linear Units (GELUs)","created":"2016-06-27","cited_by_count":3502},{"id":"1709.07871","title":"FiLM: Visual Reasoning with a General Conditioning Layer","created":"2017-09-22","cited_by_count":2333},{"id":"1802.01436","title":"Variational image compression with a scale hyperprior","created":"2018-02-01","cited_by_count":935},{"id":"1611.01704","title":"End-to-end Optimized Image Compression","created":"2016-11-05","cited_by_count":696},{"id":"1809.02736","title":"Joint Autoregressive and Hierarchical Priors for Learned Image Compression","created":"2018-09-08","cited_by_count":664},{"id":"2001.01568","title":"Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules","created":"2020-01-06","cited_by_count":590},{"id":"2111.11426","title":"Neural Fields in Visual Computing and Beyond","created":"2021-11-22","cited_by_count":540},{"id":"2203.10886","title":"ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding","created":"2022-03-21","cited_by_count":301},{"id":"1703.00395","title":"Lossy Image Compression with Compressive Autoencoders","created":"2017-03-01","cited_by_count":294},{"id":"2011.03029","title":"CompressAI: a PyTorch library and evaluation platform for end-to-end compression research","created":"2020-11-05","cited_by_count":276},{"id":"2110.13903","title":"NeRV: Neural Representations for Videos","created":"2021-10-26","cited_by_count":256},{"id":"2103.03123","title":"COIN: COmpression with Implicit Neural representations","created":"2021-03-03","cited_by_count":233},{"id":"2109.15047","title":"Deep Contextual Video Compression","created":"2021-09-30","cited_by_count":221},{"id":"2103.15306","title":"Checkerboard Context Model for Efficient Learned Image Compression","created":"2021-03-29","cited_by_count":202},{"id":"2302.14402","title":"Neural Video Compression with Diverse Contexts","created":"2023-02-28","cited_by_count":165},{"id":"2112.04267","title":"Implicit Neural Representations for Image Compression","created":"2021-12-08","cited_by_count":162},{"id":"2203.08450","title":"The Devil Is in the Details: Window-based Attention for Image Compression","created":"2022-03-16","cited_by_count":147},{"id":"2207.05894","title":"Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression","created":"2022-07-13","cited_by_count":128},{"id":"2111.13850","title":"Temporal Context Mining for Learned Video Compression","created":"2021-11-27","cited_by_count":117},{"id":"2206.07707","title":"Variable Bitrate Neural Fields","created":"2022-06-15","cited_by_count":117},{"id":"2304.02633","title":"HNeRV: A Hybrid Neural Representation for Videos","created":"2023-04-05","cited_by_count":100},{"id":"2211.07273","title":"MLIC: Multi-Reference Entropy Model for Learned Image Compression","created":"2022-11-14","cited_by_count":84},{"id":"2006.04240","title":"Improving Inference for Neural Image Compression","created":"2020-06-07","cited_by_count":83},{"id":"2201.12904","title":"COIN++: Neural Compression Across Modalities","created":"2022-01-30","cited_by_count":82},{"id":"2202.06533","title":"An Introduction to Neural Data Compression","created":"2022-02-14","cited_by_count":79},{"id":"2207.08132","title":"E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context","created":"2022-07-17","cited_by_count":76},{"id":"2206.07307","title":"VCT: A Video Compression Transformer","created":"2022-06-15","cited_by_count":74},{"id":"2003.11282","title":"Content Adaptive and Error Propagation Aware Deep Video Compression","created":"2020-03-25","cited_by_count":72},{"id":"2306.09818","title":"HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation","created":"2023-06-16","cited_by_count":71},{"id":"2211.16386","title":"Compressing Volumetric Radiance Fields to 1 MB","created":"2022-11-29","cited_by_count":68},{"id":"2006.09952","title":"Universally Quantized Neural Compression","created":"2020-06-17","cited_by_count":64},{"id":"2104.04523","title":"Compressive Neural Representations of Volumetric Scalar Fields","created":"2021-04-11","cited_by_count":64},{"id":"2212.05458","title":"COOL-CHIC: Coordinate-based Low Complexity Hierarchical Image Codec","created":"2022-12-11","cited_by_count":51},{"id":"2212.14593","title":"NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling","created":"2022-12-30","cited_by_count":51},{"id":"2302.05071","title":"EVC: Towards Real-Time Neural Image Compression with Mask Decay","created":"2023-02-10","cited_by_count":49},{"id":"2110.14678","title":"Meta-Learning Sparse Implicit Neural Representations","created":"2021-10-27","cited_by_count":48},{"id":"2212.12294","title":"FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videos","created":"2022-12-23","cited_by_count":46},{"id":"1906.01223","title":"Content Adaptive Optimization for Neural Image Compression","created":"2019-06-04","cited_by_count":40},{"id":"2101.08687","title":"Overfitting for Fun and Profit: Instance-Adaptive Data Compression","created":"2021-01-21","cited_by_count":38},{"id":"1912.08771","title":"Computationally Efficient Neural Image Compression","created":"2019-12-18","cited_by_count":32},{"id":"2208.03742","title":"PS-NeRV: Patch-wise Stylized Neural Representations for Videos","created":"2022-08-07","cited_by_count":32},{"id":"2210.12538","title":"Compressing multidimensional weather and climate data into neural networks","created":"2022-10-22","cited_by_count":31},{"id":"2309.15848","title":"SHACIRA: Scalable HAsh-grid Compression for Implicit Neural Representations","created":"2023-09-27","cited_by_count":31},{"id":"2207.14678","title":"AlphaVC: High-Performance and Efficient Learned Video Compression","created":"2022-07-29","cited_by_count":28},{"id":"2305.19185","title":"Compression with Bayesian Implicit Neural Representations","created":"2023-05-30","cited_by_count":25},{"id":"2304.06244","title":"Computationally-Efficient Neural Image Compression with Shallow Decoders","created":"2023-04-13","cited_by_count":23},{"id":"2205.08957","title":"Meta-Learning Sparse Compression Networks","created":"2022-05-18","cited_by_count":22},{"id":"2301.09479","title":"Modality-Agnostic Variational Compression of Implicit Neural Representations","created":"2023-01-23","cited_by_count":22},{"id":"2209.01019","title":"On Quantizing Implicit Neural Representations","created":"2022-09-01","cited_by_count":20},{"id":"2111.08988","title":"LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks","created":"2021-11-17","cited_by_count":19},{"id":"2207.08338","title":"MobileCodec: Neural Inter-frame Video Compression on Mobile Devices","created":"2022-07-18","cited_by_count":19},{"id":"2111.10302","title":"Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set","created":"2021-11-19","cited_by_count":18},{"id":"2306.12957","title":"Siamese SIREN: Audio Compression with Implicit Neural Representations","created":"2023-06-22","cited_by_count":13},{"id":"2307.12706","title":"Low-complexity Overfitted Neural Image Codec","created":"2023-07-24","cited_by_count":13},{"id":"2310.01258","title":"MobileNVC: Real-time 1080p Neural Video Compression on a Mobile Device","created":"2023-10-02","cited_by_count":13},{"id":"2308.07733","title":"Dynamic Low-Rank Instance Adaptation for Universal Neural Image Compression","created":"2023-08-15","cited_by_count":10},{"id":"2303.03028","title":"RQAT-INR: Improved Implicit Neural Image Compression","created":"2023-03-06","cited_by_count":9},{"id":"2309.17182","title":"RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations","created":"2023-09-29","cited_by_count":9},{"id":"2311.12821","title":"Advancing The Rate-Distortion-Computation Frontier For Neural Image Compression","created":"2023-09-26","cited_by_count":9},{"id":"2208.01602","title":"Lossy compression of multidimensional medical images using sinusoidal activation networks: an evaluation study","created":"2022-08-02","cited_by_count":5},{"id":"2207.04144","title":"L$_0$onie: Compressing COINs with L$_0$-constraints","created":"2022-07-08","cited_by_count":4},{"id":"2210.14974","title":"SINCO: A Novel structural regularizer for image compression using implicit neural representations","created":"2022-10-26","cited_by_count":4}],"next_cursor":null}