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cs.LG2024
HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
Eric Hedlin, Munawar Hayat, Fatih Porikli +2
To efficiently adapt large models or to train generative models of neural representations, Hypernetworks have drawn interest. While hypernetworks work well, training them is cumber…
cs.GR2024
NESI: Shape Representation via Neural Explicit Surface Intersection
Congyi Zhang, Jinfan Yang, Eric Hedlin +5
Compressed representations of 3D shapes that are compact, accurate, and can be processed efficiently directly in compressed form, are extremely useful for digital media application…