4 citations · 14 across the 13 of their papers we have counts for
13 papers
Understanding Rate-Distortion Performance in Distributed Transformer Inference
Anderson de Andrade, Alon Harell, Ivan V. Bajić
Transformers achieve superior performance on many tasks, but impose heavy compute and memory requirements during inference. This inference can be made more efficient by partitionin…
Lossy Common Information in a Learnable Gray-Wyner Network
Anderson de Andrade, Alon Harell, Ivan V. Bajić
Many computer vision tasks share substantial overlapping information, yet conventional codecs tend to ignore this, leading to redundant and inefficient representations. The Gray-Wy…
How Universal Are SAM2 Features?
Masoud Khairi Atani, Alon Harell, Hyomin Choi +3
The trade-off between general-purpose foundation vision models and their specialized counterparts is critical for efficient feature coding design and is not yet fully understood. W…
Base Layer Efficiency in Scalable Human-Machine Coding
Yalda Foroutan, Alon Harell, Anderson de Andrade +1
A basic premise in scalable human-machine coding is that the base layer is intended for automated machine analysis and is therefore more compressible than the same content would be…
VVC+M: Plug and Play Scalable Image Coding for Humans and Machines
Alon Harell, Yalda Foroutan, Ivan V. Bajic
Compression for machines is an emerging field, where inputs are encoded while optimizing the performance of downstream automated analysis. In scalable coding for humans and machine…
Rate-Distortion Theory in Coding for Machines and its Application
Alon Harell, Yalda Foroutan, Nilesh Ahuja +6
Recent years have seen a tremendous growth in both the capability and popularity of automatic machine analysis of images and video. As a result, a growing need for efficient compre…