5 papers
Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment
Janek Haberer, Jon Eike Wilhelm, Olaf Landsiedel
Deploying vision models across devices with varying resource constraints, or even on a single device where available compute fluctuates due to battery state, thermal throttling, or…
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…
MCUCoder: Adaptive Bitrate Learned Video Compression for IoT Devices
Ali Hojjat, Janek Haberer, Olaf Landsiedel
The rapid growth of camera-based IoT devices demands the need for efficient video compression, particularly for edge applications where devices face hardware constraints, often wit…