{"work":{"id":"ce10c9d6-c0df-421e-a2d7-d98f084a14ba","openalex_id":null,"doi":null,"arxiv_id":"1802.01436","raw_key":null,"title":"Variational image compression with a scale hyperprior","authors":null,"authors_text":"Johannes Ballé, David Minnen, Saurabh Singh, Sung Jin Hwang, and Nick John- ston","year":2018,"venue":"eess.IV","abstract":"We describe an end-to-end trainable model for image compression based on variational autoencoders. The model incorporates a hyperprior to effectively capture spatial dependencies in the latent representation. This hyperprior relates to side information, a concept universal to virtually all modern image codecs, but largely unexplored in image compression using artificial neural networks (ANNs). Unlike existing autoencoder compression methods, our model trains a complex prior jointly with the underlying autoencoder. We demonstrate that this model leads to state-of-the-art image compression when measuring visual quality using the popular MS-SSIM index, and yields rate-distortion performance surpassing published ANN-based methods when evaluated using a more traditional metric based on squared error (PSNR). Furthermore, we provide a qualitative comparison of models trained for different distortion metrics.","external_url":"https://arxiv.org/abs/1802.01436","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-05-25T10:50:39.195418+00:00","pith_arxiv_id":"1802.01436","created_at":"2026-05-11T09:21:01.377352+00:00","updated_at":"2026-05-25T10:50:39.195418+00:00","title_quality_ok":true,"display_title":"Variational image compression with a scale hyperprior","render_title":"Variational image compression with a scale hyperprior"},"hub":{"state":{"work_id":"ce10c9d6-c0df-421e-a2d7-d98f084a14ba","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":13,"external_cited_by_count":null,"distinct_field_count":8,"first_pith_cited_at":"2019-07-02T14:16:37+00:00","last_pith_cited_at":"2026-05-17T15:18:20+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-05-30T18:21:28.021321+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":3},{"context_role":"method","n":1}],"polarity_counts":[{"context_polarity":"background","n":3},{"context_polarity":"use_method","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}