Feisst, M.
* 2004: Dynamically optimised 3D (virtual reality) data transmission for mobile devices
Feist, C.
* 1997: Detection of the objects with given shape on the grey-valued pictures
* 1997: Extraction of filled-in data from colour forms
Feist, D.G.[Dietrich G.]
* 2020: Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from TROPOMI
* 2022: Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment
Feiszli, M.[Matt]
* 2017: Numerical Computation of Weil-Peterson Geodesics in the Universal Teichmüller Space
* 2018: Scenes-Objects-Actions: A Multi-task, Multi-label Video Dataset
* 2019: Video Classification With Channel-Separated Convolutional Networks
* 2020: Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias
* 2020: SF-net: Single-frame Supervision for Temporal Action Localization
* 2020: Video Modeling With Correlation Networks
* 2020: What Makes Training Multi-Modal Classification Networks Hard?
* 2021: FP-NAS: Fast Probabilistic Neural Architecture Search
* 2021: Generic Event Boundary Detection: A Benchmark for Event Segmentation
* 2021: Only Time Can Tell: Discovering Temporal Data for Temporal Modeling
* 2021: Searching for Two-Stream Models in Multivariate Space for Video Recognition
* 2021: Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
* 2022: GEB+: A Benchmark for Generic Event Boundary Captioning, Grounding and Retrieval
* 2022: Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity
* 2023: Relational Space-Time Query in Long-Form Videos
* 2023: Self-Supervised Object Detection from Egocentric Videos
* 2023: SiLK: Simple Learned Keypoints
Includes: Feiszli, M.[Matt] Feiszli, M.
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