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Research questionHow can discrete visual quantizers be compared fairly at matched coding rates?Discrete visual quantizers can appear better or worse depending on token count, codebook size, latent feature statistics, and which metric is emphasized. A fair comparison must separate coding rate from reconstruction fidelity and account for these differing conditions.
AI
Computer Vision
Evaluation & Benchmarks
Image & Video Processing
Machine Learning
Research Paper
Latest papersRecent research connected to this question, newest first.A Unified Rate-Distortion Perspective on Vector, Product, and Scalar QuantizationThe source develops a rate–distortion framework for vector, product, and scalar quantization. It defines nominal fixed-length rate from token count and codebook size, treats quantization error as distortion, and provides theoretical and empirical evidence for comparisons that control latent feature statistics and use identical coding rates.research paper · Sep 2, 2026
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