“…The experimental study evaluates the performance of deep learning-based video coding models, including STreamNet, DLIMD [18], and convLSTM [19], using five different datasets [20]: UCF10, HMDB51, Hollywood2, VID, and 20BN. The evaluation metrics include BPP, Bit Rate, PSNR [21], MS-SSIM [22], MSE, Compression Ratio, Encoding/Decoding Time, and BDBR [23]. Experiments use 10-fold cross-validation with 80% data for training, 10% for validation, and 10% for testing.…”