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Cross-check of JVET-AP0234 (AHG11: dynamic quantization and hardware optimization for NNIP)
[AHG11] On NNVC training sets
Cross-check of JVET-AO0133 (EE1-3.3: Combination of EE1-3.1 and EE1-3.2)
EE2-1.9: TMRL angle offset refinement
EE2-1.8: IntraTMP with DMVR
Cross-check of JVET-AN0083 (EE1-1.2: backbone block enhancement of LOP in-loop filter with over-parameterized training and variable channels)
AHG17: Description of NNVC-based CfE response
AHG7: Preliminary tool analysis with the criteria in JVET-AM0042 – Update on IntraTMP
Non-EE2: TMRL Angle Offset Refinement
EE2-2.5a: Combination of tests EE2-2.1, EE2-2.3b, and EE2-2.4
EE2-2.1: TMRL blend
EE2-1.11: a combination of EE2-1.2c and EE2-1.6a
EE2-1.6: Intra Merge Mode
Cross-check of JVET-AM0172 (EE2-3.5: a combination of EE2-3.3 and EE2-3.4)
EE2-1.2a/b/c: TIMD-BV extension with enhanced IntraTMP merge list
EE2-1.12: a combination of EE2-1.2c, EE2-1.6a and EE2-1.3
EE2-1.5: combination of EE2-1.1 and EE2-1.4
EE2-1.4: combination of EE2-1.2c and EE2-1.3
EE2-1.3: Intra TMP sub-modes depending on the template type information
Non-EE2: Enhanced DD-CCP and CCP-Merge Fusion
EE2-1.1: TIMD fusion with neural network based intra prediction
Cross-check of JVET-AL0112 (Non-EE2: third transform set selection for intraNN)
[AHG12] Combination of JVET-AL0174, JVET-AL0195 and JVET-AL0241 on Enhanced TIMD with NNIP and Optimized Block Vector Derivation
Non-EE2: TIMD fusion with neural network based intra prediction
Non-EE2: Intra TMP sub-modes depending on the template type information
EE1-3.1: NNVC-LOP4 and LOP5 retraining with additional BVI-AOM dataset
Non-EE2: TIMD-BV extension with enhanced IntraTMP merge list
Crosscheck of JVET-AK0150 (EE1-1.2: LOP with improved Attention and residual groups)
Crosscheck of JVET-AK0139 (EE1-1.3 : multiscale blocks in LOP4 and VLOP3 filters)
EE2-1.3: IntraTMP merge candidates enrichment
AHG7: Complexity and memory footprint assessment of PDP, Neural Network-based Intra Prediction, MTS and LFNST/NSPT, and ALF in ECM-15
EE2-2.20_2.21: Neural network-based intra prediction with DIMD mode derivation
EE1 related: EE1-2.3 Block based QP information in NN loop filters additional results
AhG14: SADL implementation improvements for sparse models
AHG12: Intra TMP improvements
AhG12: Neural network-based intra prediction with DIMD mode derivation
EE1-2.3: Block based QP information in NN loop filters
Crosscheck of JVET-AJ0182 (EE1-1.5: Multiscale blocks in LOP3 and VLOP2 filter)
EE1-5.1 : combination of the neural network-based intra prediction mode and ISP
AHG12 : neural network-based intra prediction
Cross-check of JVET-AI0159 (EE2-2.9: derived MIP modes with fusion (sub-test EE2-2.9b))
EE2-2.6: IntraTMP candidates with overlapping refinement window enhanced
EE2-1.1: adaptive dual tree in inter Slices
Cross-check of JVET-AI0087 (EE2-1.2: restricting BT CUs to apply QT-like partitioning structure)
AhG11: Block based QP information in NN loop filters
Cross-check of JVET-AH0058 (Non-EE2 : derived MIP modes with fusion)
Crosscheck of JVET-AH0195 (EE1-related : complexity reduction of NN in-loop filters through early cropping)
AHG11 : combination of the neural network-based intra prediction mode and ISP
Ahg12: adaptive dual-tree coding in B slices
AhG11: LOP/HOP ablation study
EE2-related: IntraTMP merge candidates clustering based on refinement window
AHG12 : Neural Network-based Intra Prediction
EE2-2.10f: MR-SAD/SATD based IntraTMP BV search with signalling and BV reordering
EE2-2.10c: MR-SAD based IntraTMP BV search with signalling
EE2-2.10h: MR-SAD/SATD based IntraTMP BV search with signalling and BV reordering with ARBVP for IntraTMP merge
AhG14: SADL update
AhG11: LOP/HOP training strategy study
AhG14 SADL update
AHG12: Additional Metric for IntraTMP
EE2-1.2: IntraTMP with Merge Candidates
EE2-1.4: IntraTMP extension to DIMD
EE2-1.6/1.7a/1.7b: combinations of tests 1.2, 1.3, 1.4 and 1.5
EE2-1.5: IntraTMP extension to LIC
EE2-1.7b related: unrestricted 1.7b performances
AhG11: on HOP learning rate
AhG11: on HOP luma/chroma balance
Crosscheck of JVET-AF0108 (EE2-1.1: Non-square quadtree partitioning)
AHG12: Intra TMP extension to DIMD, LIC and SGPM
EE2-related : complete results for EE2-1.1b in JVET-AF0249
AhG11: on HOP batch size
Cross-check of JVET-AF0111 (AHG10 : MTT split modes early termination)
Cross-check of JVET-AF0085 (EE1-1.2.1: on residual adjustments of NNLF)
EE1-3.1: Neural network-based intra prediction with reduced complexity
AhG14: SADL update
EE1-6.1: Neural network-based intra prediction with reduced complexity
AhG14: SADL update
Non-EE2: Reference sample interpolation for intra prediction
Cross-check of JVET-AD0189: a simplified NN-based RDO model for Filter-Set #1
AhG11 : neural network-based intra prediction with reduced complexity
AhG14: SADL v5 changes
AhG14 SADL v4 changes
Cross-check of JVET-AC0126 : EE1-related : reduced complexity through channel redistribution in NN head
EE2-1.11c: Combination of EE2-1.7, EE2-1.8, EE2-1.9, and EE2-1.10
Cross-check of EE2-1.13 : CCCM using non-downsampled luma samples
EE2-1.10: Optimizing the use of reference samples
EE1-3.2 : neural network-based intra prediction with learned mapping to VVC intra prediction modes
EE2-1.11b: Combination of Test 1.8, Test 1.9 and Test 1.10
Cross-check of JVET-AB0116: “AHG12 - Location-dependent Decoder-side Intra Mode Derivation
Non-EE2: optimizing the use of available decoded reference samples
EE2-related: Modifications of EE2-3.2 and EE2-3.3
EE2-3.3: Combination of EE2-3.1a and EE2-3.2
EE2-3.1a: IntraTMP for chroma component
IntraTMP for chroma Components
AHG11: Small Ad-hoc Deep-Learning Library (SADL) update
AHG9: NNR post-filter SEI message extension for flexible decoding capabilities
AhG11: SADL update
AHG11: Small Ad-hoc Deep-Learning Library (SADL) update
AhG12: Removed DIMD from MPM list of TIMD
AHG12: Neural Network-based intra prediction
AhG11: Hybrid Conventional/Deep-learning-based image coding
EE1-3.1: Intra prediction using neural networks
EE2-1.1~EE2-1.4: Tests on unsymmetric partitioning methods
AHG12: removing a discontinuity in the discrete angle comparison in DIMD
EE2: Encoder partitioning optimization for ECM and crosscheck of EE2-1.1
EE1-3.1: BD-rate gains vs complexity of NN-based intra prediction
AHG11: Small Ad-hoc Deep-Learning Library
AHG11: BD-rate gains vs complexity of NN-based intra prediction
EE2-1.5: A combining test of EE2-1.2 and EE2-1.4b
EE2-1.1 and EE2-1.2: Asymmetric Binary Tree partitioning
AHG11: Deep-learning based inter prediction blending
AHG11: Replacing SAO in-loop filter with Neural Networks
EE2 related: asymmetric binary tree splitting on top of VVC
AHG11: neural network-based intra prediction: updated signaling
AHG11: Revisiting SAO in-loop filter with Neural Networks
AHG11: Methodology additional requirements
AHG11: Neural Network-based intra prediction with transform selection in VVC
CE3-related: simplification of Matrix Intra Prediction
Cross-check of JVET-AQ0182 (EE1-4.1: adaptive quantization and hardware optimization for NNIP)