11 to 20 of 3,711 Results
Jul 1, 2026 -
JPEG AIC2026: Fine-grained image compression dataset
ZIP Archive - 8.7 GB -
MD5: f9010c61602bf631a049d167d3f4cf18
Cropped distorted images (840×944) and 70 reference crops, one per source. Superset of AIC2026-PTC-stimuli.zip. |
Jul 1, 2026 -
JPEG AIC2026: Fine-grained image compression dataset
Tabular Data - 22.0 KB - 22 Variables, 70 Observations - UNF:6:eqLJRr7Fd4d9hArfNmiCrQ==
AIC2026_source_images_metadata_and_attribution.csv: CSV file containing metadata, source information, licensing, and attribution for the 70 source images. Each row corresponds to one source image and includes the dataset image identifier, original filename, source and original dimensions, image origin, author, source URL, license, capture date, ori... |
Jul 1, 2026 -
JPEG AIC2026: Fine-grained image compression dataset
Markdown Text - 17.5 KB -
MD5: e94f57027f5ba02a14d9fa118d298181
Encoding recipes: codec configurations and operating point definitions used for the AIC4 experiment. |
Jul 1, 2026 -
JPEG AIC2026: Fine-grained image compression dataset
ZIP Archive - 8.3 GB -
MD5: 9b0a79893f08d03811aaf01d4f70c526
Learning-based codec outputs at all distortion levels. Includes learning_codecs_all_levels.csv. |
Jul 1, 2026 -
JPEG AIC2026: Fine-grained image compression dataset
ZIP Archive - 221.7 MB -
MD5: 9d13a64839c945aec9f97fb90061ba7d
source_images.zip: ZIP archive containing the 70 pristine source images used as references in AIC2026, named `S01_Ref_00.png` to `S70_Ref_00.png`. |
Jun 29, 2026 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Zhang, Lin; Zhang, Ying; Huettner, Timo; Kerle-Malcharek, Wilhelm; Klein, Karsten; Schreiber, Falk; Bulling, Andreas, 2026, "Replication Data for: Understanding and Enhancing Stereoscopic 3D Graph Perception with Eye Tracking", https://doi.org/10.18419/DARUS-5950, DaRUS, V1
Immersive Analytics (IA) utilises stereoscopic 3D (S3D) graph visualisations in Virtual and Augmented Reality to harness spatial understanding and engagement beyond 2D screen displays. Despite growing research interest, little is known about how users perceive such structures, or how their gaze behaviour relates to task performance. We address this... |
Jun 29, 2026 -
Replication Data for: Understanding and Enhancing Stereoscopic 3D Graph Perception with Eye Tracking
Markdown Text - 1.3 KB -
MD5: 06289ddbc4f1010f0af29fa5eaf8dbbc
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Jun 29, 2026 -
Replication Data for: Understanding and Enhancing Stereoscopic 3D Graph Perception with Eye Tracking
ZIP Archive - 22 B -
MD5: 76cdb2bad9582d23c1f6f4d868218d6c
gaze data, camera positions, and task answers for the Study 2 on multilayer graph |
Jun 29, 2026 -
Replication Data for: Understanding and Enhancing Stereoscopic 3D Graph Perception with Eye Tracking
ZIP Archive - 103.9 KB -
MD5: 90339a95c08c691c1d85675d137a6ff1
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Jun 29, 2026 -
Replication Data for: Understanding and Enhancing Stereoscopic 3D Graph Perception with Eye Tracking
ZIP Archive - 1.3 MB -
MD5: 4a55530504e976b46da1210b57fa0f65
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