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[AHG11] Additional Information on Stable Float Method for Neural Network Inference on GPU devices
EE1-4.4: Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
EE1-4.3: Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
EE1-4.2: Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
EE1-4.1: Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
Crosscheck of JVET-AO0204 (EE1-6.1.3 and EE1-6.2.3: JPEG-AI as a Learned End-to-End Intra Frame Codec)
Crosscheck of JVET-AO0186 (EE1-6.1.1 and EE1-6.2.1: DCVC-FM as a Learned End-to-End Intra Frame Codec)
[AHG11] Stable float convolution for neural network inference
[AHG11] A Hybrid Framework Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
EE1-6.2: Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
EE1-6.1: Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
[AHG17] Suggestions on Draft CfP, CTCs and complexity reporting
[AHG11] A Hybrid Framework Integrating End-to-End Learned Intra-Frame Codec with Conventional Codec
[AHG11/AHG14] Comparison of Multi-Layer and Single-Layer Interfaces for Hybrid End-to-End Video Coding Frameworks
AHG11: A Hybrid Framework Integrating End-to-End Learned Image Codec with Conventional Codec
[AHG11] A Hybrid Framework Integrating End-to-End Learned Image Codec with Conventional Codec
[AHG11] A Hybrid Framework Integrating End-to-End Learned Image Codec with Conventional Codec
AHG11: Neural network loop filter
Withdrawn
AHG10/AHG12: Clean-Slate NextSoftware2 implementation without future Video Coding Tools