Theme The Data Compression Conference (DCC) is an international forum for current work on data compression and related applications. Both theoretical and experimental work are of interest. Topics of interest include but are not limited to: Lossless and lossy compression for storage and transmission of specific types of data (including text, gray scale and color photographs, multi-spectral and hyper-spectral images, palette images, video, movies, audio, music, maps, instrument and sensor data, space data, earth observation data, scientific data, weather data, medical data, graphics data, geometry data, 3D representations, animation, bi-level images / bit-maps, web content, web graphs, etc.); source coding; source coding in multiple=access networks; joint source-channel coding; rate-distortion coding; rate allocation; multiple-description coding; quantization theory; vector quantization (VQ); multiple description VQ; transform-based methods (including DCT and wavelet transforms); parallel compression algorithms and hardware; error-resilient compression techniques; adaptive compression algorithms; browsing and searching compressed data; compressed data structures; applications to immersive media; inpainting-based compression; perceptual coding; visual search; object recognition; applications of neural networks and deep learning (e.g., CNNs) to compression; string searching and manipulation used in compression applications; fractal-based compression methods; information retrieval employing compression techniques; steganography / hidden information with respect to compressed data; minimal-length encoding and applications to learning; system issues relating to data compression (including error control, data security, indexing, and browsing); compression applications and issues for computational biology and bioinformatics; compression applications and issues for the internet; compression applications and issues for mobile computing; applications of compression to file distribution and software updates; applications of compression to file storage and backup systems; applications of compression to data mining; applications of compression to image retrieval; applications of compression and information theory to human-computer interaction (HCI); development of and extensions to compression standards (including the HEVC, JPEG, MPEG, H.xxx, and G.xxx families and including compression of specific image types such as plenoptic images, point cloud images, and light field images); compressed sensing / compressive sampling; and the use of techniques from information theory and data compression in networking, communications, and storage of large data sets.