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42nd Meeting: Santa Eulària, ES, April 2026 2026-04-25 09:19
EE1-4.1.3 and EE1-4.2.3: JPEG-AI as a Learned End-to-End Intra Frame Codec
Abstract
This contribution reports the EE1-4.1.3 and EE1-4.2.3 results. In both experiments, JPEG-AI is used as an external coder, which feeds I-frames to VTM using the hybrid multilayer framework is available in NNVC16. In EE1-4.1.3, residual coding on top of the prediction for end-to-end AI coded reference picture is enabled. In EE1-4.2.3, skip mode is forced (by setting the QP of Intra frames to the maximum, thus the reconstruction is identical to the externally end-to-end AI coded frame. The complexity of JPEG-AI decoder is 22 kMACs per pixel and has about 5M parameters. BD-rate performance and complexity vs. NNVC15 (with all NN tools off, identical to VTM 23.13) are the following:
JVET-AP0232 EE1-4.1.3 and EE1-4.2.3: JPEG-AI as a Learned End-to-End Intra Frame Codec [A. Karabutov, P. Jia, E. Alshina (Huawei)]

EE1 related and beyond-EE contributions: Neural network-based video coding (10)

Contributions in this area were discussed during 1430–1815 on Saturday 25 April 2026 (chaired by JRO).

Decisions
Contributions in this area were discussed during 1430–1815 on Saturday 25 April 2026 (chaired by JRO).
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