8 citations · 16 across the 7 of their papers we have counts for
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cs.CV2023★ 4 cited
Does Image Anonymization Impact Computer Vision Training?
Håkon Hukkelås, Frank Lindseth
Image anonymization is widely adapted in practice to comply with privacy regulations in many regions. However, anonymization often degrades the quality of the data, reducing its ut…
cs.CV2023★ 1 cited
Synthesizing Anyone, Anywhere, in Any Pose
Håkon Hukkelås, Frank Lindseth
We address the task of in-the-wild human figure synthesis, where the primary goal is to synthesize a full body given any region in any image. In-the-wild human figure synthesis has…
cs.CV2023
FullFormer: Generating Shapes Inside Shapes
Tejaswini Medi, Jawad Tayyub, Muhammad Sarmad +2
Implicit generative models have been widely employed to model 3D data and have recently proven to be successful in encoding and generating high-quality 3D shapes. This work builds…