2025
DeepCompress-ViT: Rethinking Model Compression to Enhance Efficiency of Vision Transformers at the Edge
Sabbir Ahmed, Abdullah Al Arafat, Deniz Najafi, Akhlak Mahmood, Mamshad Nayeem Rizve, Mohaiminul Al Nahian +3
CVPR 2025poster
Vision Transformers (ViTs) excel in tackling complex vision tasks, yet their substantial size poses significant challenges for applications on resource-constrained edge devices. The increased size of these models leads to higher overhead (e.g., energy, latency) when transmitting model weights betwee…