10 citations · 11 across the 11 of their papers we have counts for
11 papers
Prompt-Guided Prefiltering for VLM Image Compression
Bardia Azizian, Ivan V. Bajic
The rapid progress of large Vision-Language Models (VLMs) has enabled a wide range of applications, such as image understanding and Visual Question Answering (VQA). Query images ar…
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…
Metaverse: A Young Gamer's Perspective
Ivan V. Bajić, Teo Saeedi-Bajić, Kai Saeedi-Bajić
When developing technologies for the Metaverse, it is important to understand the needs and requirements of end users. Relatively little is known about the specific perspectives on…
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…
Grad-FEC: Unequal Loss Protection of Deep Features in Collaborative Intelligence
Korcan Uyanik, S. Faegheh Yeganli, Ivan V. Bajić
Collaborative intelligence (CI) involves dividing an artificial intelligence (AI) model into two parts: front-end, to be deployed on an edge device, and back-end, to be deployed in…
Learned Scalable Video Coding For Humans and Machines
Hadi Hadizadeh, Ivan V. Bajić
Video coding has traditionally been developed to support services such as video streaming, videoconferencing, digital TV, and so on. The main intent was to enable human viewing of…
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A Survey
Hanieh Naderi, Ivan V. Bajić
Deep learning has successfully solved a wide range of tasks in 2D vision as a dominant AI technique. Recently, deep learning on 3D point clouds is becoming increasingly popular for…
Conditional and Residual Methods in Scalable Coding for Humans and Machines
Anderson de Andrade, Alon Harell, Yalda Foroutan +1
We present methods for conditional and residual coding in the context of scalable coding for humans and machines. Our focus is on optimizing the rate-distortion performance of the…
Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations
Zahra Hafezi Kafshgari, Chamani Shiranthika, Parvaneh Saeedi +1
SplitFed Learning, a combination of Federated and Split Learning (FL and SL), is one of the most recent developments in the decentralized machine learning domain. In SplitFed learn…
Multi-Task Learning for Screen Content Image Coding
Rashid Zamanshoar Heris, Ivan V. Bajić
With the rise of remote work and collaboration, compression of screen content images (SCI) is becoming increasingly important. While there are efficient codecs for natural images,…
LCCM-VC: Learned Conditional Coding Modes for Video Compression
Hadi Hadizadeh, Ivan V. Bajić
End-to-end learning-based video compression has made steady progress over the last several years. However, unlike learning-based image coding, which has already surpassed its handc…