12 citations · 15 across the 7 of their papers we have counts for
4 papers · 1 filter
ThinkingViT: Matryoshka Thinking Vision Transformer for Elastic Inference
Ali Hojjat, Janek Haberer, Soren Pirk +1
ViTs deliver SOTA performance, yet their fixed computational budget prevents scalable deployment across heterogeneous hardware. Recent Matryoshka-style Transformer architectures mi…
LimitNet: Progressive, Content-Aware Image Offloading for Extremely Weak Devices & Networks
Ali Hojjat, Janek Haberer, Tayyaba Zainab +1
IoT devices have limited hardware capabilities and are often deployed in remote areas. Consequently, advanced vision models surpass such devices' processing and storage capabilitie…
HydraViT: Stacking Heads for a Scalable ViT
Janek Haberer, Ali Hojjat, Olaf Landsiedel
The architecture of Vision Transformers (ViTs), particularly the Multi-head Attention (MHA) mechanism, imposes substantial hardware demands. Deploying ViTs on devices with varying…
ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training
Ali Hojjat, Janek Haberer, Olaf Landsiedel
Progressive compression allows images to start loading as low-resolution versions, becoming clearer as more data is received. This increases user experience when, for example, netw…