Work

Spline-Based Transformers

Year: 2024

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-031-73016-0_1

Authors: Prashanth Chandran, Agon Serifi, Markus Gross, Moritz Bächer

Institutions: ETH Zurich, Walt Disney (Switzerland), Walt Disney (United States)

Language: English

Topic: Generative Adversarial Networks and Image Synthesis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4403764502

FWCI:

Cites: 34

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Related to: 10