17 citations · 99 across the 66 of their papers we have counts for
Showing 2023 · cs.CVShow all
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cs.CV2023★ 1 cited
CrAFT: Compression-Aware Fine-Tuning for Efficient Visual Task Adaptation
Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi +1
Transfer learning has become a popular task adaptation method in the era of foundation models. However, many foundation models require large storage and computing resources, which…
cs.CV2023★ 1 cited
Training-Free Acceleration of ViTs with Delayed Spatial Merging
Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi +1
Token merging has emerged as a new paradigm that can accelerate the inference of Vision Transformers (ViTs) without any retraining or fine-tuning. To push the frontier of training-…