Update the audio fusion result with a better tsn-f3 result. (#281)

* Update the fusion result with a better tsn-f3 result.

* Fix multi blank.

* Update changelog.

Update config link.

configs/recognition_audio/resnet/README.md

@@ -14,10 +14,10 @@
 
 ### Kinetics-400
 
-|config | n_fft | gpus | backbone |pretrain| top1 acc| top5 acc | inference_time(video/s) | gpu_mem(M)| ckpt | log| json|
+|config | n_fft | gpus | backbone |pretrain| top1 acc/delta| top5 acc/delta | inference_time(video/s) | gpu_mem(M)| ckpt | log| json|
 |:--|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 |[tsn_r18_64x1x1_100e_kinetics400_audio_feature](/configs/recognition_audio/resnet/tsn_r18_64x1x1_100e_kinetics400_audio_feature.py)|1024|8| ResNet18 | None |19.7|35.75|x|1897|[ckpt](https://download.openmmlab.com/mmaction/recognition/audio_recognition/tsn_r18_64x1x1_100e_kinetics400_audio_feature/tsn_r18_64x1x1_100e_kinetics400_audio_feature_20201012-bf34df6c.pth)|[log](https://download.openmmlab.com/mmaction/recognition/audio_recognition/tsn_r18_64x1x1_100e_kinetics400_audio_feature/20201010_144630.log)|[json](https://download.openmmlab.com/mmaction/recognition/audio_recognition/tsn_r18_64x1x1_100e_kinetics400_audio_feature/20201010_144630.log.json)|
-|[tsn_r18_64x1x1_100e_kinetics400_audio_feature](/configs/recognition_audio/resnet/tsn_r18_64x1x1_100e_kinetics400_audio_feature.py) + [tsn_r50_1x1x3_100e_kinetics400_rgb](/configs/recognition/tsn/tsn_r50_1x1x3_100e_kinetics400_rgb.py)|1024|8| ResNet(18+50) | None |70.01|88.71|x|x|x|x|x|
+|[tsn_r18_64x1x1_100e_kinetics400_audio_feature](/configs/recognition_audio/resnet/tsn_r18_64x1x1_100e_kinetics400_audio_feature.py) + [tsn_r50_video_320p_1x1x3_100e_kinetics400_rgb](/configs/recognition/tsn/tsn_r50_video_320p_1x1x3_100e_kinetics400_rgb.py)|1024|8| ResNet(18+50) | None |71.50(+0.39)|90.18(+0.14)|x|x|x|x|x|
 
 Notes:
 
@@ -61,3 +61,13 @@ python tools/test.py configs/audio_recognition/tsn_r50_64x1x1_100e_kinetics400_a
 ```
 
 For more details, you can refer to **Test a dataset** part in [getting_started](/docs/getting_started.md#test-a-dataset).
+
+## Fusion
+For multi-modality fusion, you can use the simple [script](/tools/analysis/report_accuracy.py), the standard usage is:
+
+```shell
+python tools/analysis/report_accuracy.py --scores ${AUDIO_RESULT_PKL} ${VISUAL_RESULT_PKL} --datalist data/kinetics400/kinetics400_val_list_rawframes.txt --coefficient 1 1
+```
+
++ AUDIO_RESULT_PKL: The saved output file of `tools/test.py` by the argument `--out`.
++ VISUAL_RESULT_PKL: The saved output file of `tools/test.py` by the argument `--out`.

docs/changelog.md

@@ -18,6 +18,7 @@
 - Rename the old evaluating protocol `mean_average_precision` as `mmit_mean_average_precision` since it is only used on MMIT and is not the `mAP` we usually talk about. Add `mean_average_precision`, which is the real `mAP` ([#235](https://github.com/open-mmlab/mmaction2/pull/235))
 - Add accurate setting (Three crop * 2 clip) and report corresponding performance for TSM model ([#241](https://github.com/open-mmlab/mmaction2/pull/241))
 - Add citations in each preparing_dataset.md in `tools/data/dataset` ([#289](https://github.com/open-mmlab/mmaction2/pull/289))
+- Update the performance of audio-visual fusion on Kinetics-400 ([#281](https://github.com/open-mmlab/mmaction2/pull/281))
 
 **Bug Fixes**
 - Register `FrameSelector` in `PIPELINES` ([#268](https://github.com/open-mmlab/mmaction2/pull/268))