41 citations · 46 across the 6 of their papers we have counts for
8 papers
Feature Compression for Machines with Range-Based Channel Truncation and Frame Packing
Juan Merlos, Fabien Racapé, Hyomin Choi +2
This paper proposes a method that enhances the compression performance of the current model under development for the upcoming MPEG standard on Feature Coding for Machines (FCM). T…
Efficient Feature Compression for Machines with Global Statistics Preservation
Md Eimran Hossain Eimon, Hyomin Choi, Fabien Racapé +4
The split-inference paradigm divides an artificial intelligence (AI) model into two parts. This necessitates the transfer of intermediate feature data between the two halves. Here,…
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…
Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction Offsets
Fatih Kamisli, Fabien Racape, Hyomin Choi
Achieving successful variable bitrate compression with computationally simple algorithms from a single end-to-end learned image or video compression model remains a challenge. Many…
Learned Disentangled Latent Representations for Scalable Image Coding for Humans and Machines
Ezgi Ozyilkan, Mateen Ulhaq, Hyomin Choi +1
As an increasing amount of image and video content will be analyzed by machines, there is demand for a new codec paradigm that is capable of compressing visual input primarily for…
Frequency-aware Learned Image Compression for Quality Scalability
Hyomin Choi, Fabien Racape, Shahab Hamidi-Rad +2
Spatial frequency analysis and transforms serve a central role in most engineered image and video lossy codecs, but are rarely employed in neural network (NN)-based approaches. We…
CNN-based driving of block partitioning for intra slices encoding
Franck Galpin, Fabien Racapé, Sunil Jaiswal +3
This paper provides a technical overview of a deep-learning-based encoder method aiming at optimizing next generation hybrid video encoders for driving the block partitioning in in…
End-to-end optimized image compression for machines, a study
Lahiru D. Chamain, Fabien Racapé, Jean Bégaint +2
An increasing share of image and video content is analyzed by machines rather than viewed by humans, and therefore it becomes relevant to optimize codecs for such applications wher…