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39th Meeting: Daejeon, KR, June 2025 2025-06-24 22:45
JVET AHG report: Optimization of encoders and receiving systems for machine analysis of coded video content (AHG8)
Abstract
This document summarizes the activities of AHG 8: Optimization of encoders and receiving systems for machine analysis of coded video content between the 38th meeting (26 March–04 April 2025) being held online and the 39th meeting (26 June – 4 July 2025) held in Daejeon, KR.
JVET-AM0008 JVET AHG report: Optimization of encoders and receiving systems for machine analysis of coded video content (AHG8) [S. Liu, J. Ström, S. Wang, M. Zhou (AHG chairs)]

Software and Common Test Conditions

AHG 8 related software and documents can be accessed at https://vcgit.hhi.fraunhofer.de/jvet-ahg-ofm. This repository contains two projects: common test conditions, reporting templates with anchor results, evaluation scripts and task networks are available in https://vcgit.hhi.fraunhofer.de/jvet-ahg-ofm/ofm-ctc, and software implementation examples are hosted in https://vcgit.hhi.fraunhofer.de/jvet-ahg-ofm/vtm-ofm. For this meeting cycle, common test conditions remain unchanged as described in output document JVET-AI2031.

Technical Report

The 9th draft of the technical report (TR) JVET-AL2030 “Optimization of encoders and receiving systems for machine analysis of coded video content (draft 9)” was produced and uploaded to JVET document system on 2025-04-30, including the following additions on top of draft 8:

  • Updated to address comments in m72107
  • Tool combination example (to Annex B) JVET-AL0152

The following combined tool examples have been included in the submitted DTR, besides single tool implementation examples.

Technology 1

Technology 2

Technology 3

Technology 4

Technology 5

Adaptive QP (8.1 and A.1)

Temporal layer QP offset (8.2)

De-noising filter (7.5)

Temporal layer QP offset (8.2)

Pre-processing (7.2 and A.2)

NNPF (9.3 and A.3)

4:4:4 coding (8)

Reduced resolution (Clauses 7.4 and 9.2)

Pre-processing (7.2 and A.2)

NNPF (9.3 and A.3)

Adaptive QP (8.1 and A.1)

NNPF (9.3 and A.3)

Adaptive QP (8.1 and A.1)

NNPF (9.3 and A.3)

Reduced resolution (Clauses 7.4 and 9.2)

Pre-processing (7.2 and A.2)

NNPF (9.3 and A.3)

Adaptive QP (8.1 and A.1)

Temporal layer QP offset (8.2)

Pre-processing (7.2 and A.2)

NNPF (9.3 and A.3)

Adaptive QP (8.1 and A.1)

Temporal resampling (9.1 and A.4)

Pre-processing (7.2 and A.2)

NNPF (9.3 and A.3)

Adaptive QP (8.1 and A.1)

Temporal resampling (9.1 and A.4)

Temporal layer QP offset (8.2)

Input contributions

There were no input contributions related to AHG 8 mandates (by the time the AHG report was uploaded) except the report itself.

Recommendations

The AHG recommended to:

  • Continue improving the on-going TR document based on feedback.
  • Discuss plan and timeline for finalization of TR (version 1).
  • Continue investigating non-normative technologies and their uses for machine vision applications and machine consumptions.
Decisions
The AHG recommended to: Continue improving the on-going TR document based on feedback. Discuss plan and timeline for finalization of TR (version 1). Continue investigating non-normative technologies and their uses for machine vision applications and machine consumptions.
Citation