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Found 6 papers, 1 papers with code
A Perspective on Deep Vision Performance with Standard Image and Video Codecs
The use of standardized codecs, such as JPEG or H. 264, is prevalent and required to ensure interoperability.
iRAG: An Incremental Retrieval Augmented Generation System for Videos
Use of RAG for combined understanding of multimodal data such as text, images and videos is appealing but two critical limitations exist: one-time, upfront capture of all content in large multimodal data as text descriptions entails high processing times, and not all information in the rich multimodal data is typically in the text descriptions.
Differentiable JPEG: The Devil is in the Details
the input image, the JPEG quality, the quantization tables, and the color conversion parameters.
LeanContext: Cost-Efficient Domain-Specific Question Answering Using LLMs
Additionally, if free pretrained LLM-based summarizers are used to reduce context (into human consumable summaries), LeanContext can further modify the reduced context to enhance the accuracy (ROUGE-1 score) by $13. 22\%$ to $24. 61\%$.
Deep Video Codec Control for Vision Models
To overcome the deterioration of vision performance, this paper presents the first end-to-end learnable deep video codec control that considers both bandwidth constraints and downstream deep vision performance, while adhering to existing standardization.
F3S: Free Flow Fever Screening
Identification of people with elevated body temperature can reduce or dramatically slow down the spread of infectious diseases like COVID-19.
