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Model Zoo

Environment and Settings

  • 4/1 NVIDIA V100 GPUs for training/evaluation.
  • Auto-mixed precision was enabled in training but disabled in evaluation.
  • Test-time augmentations were not used.
  • The inference resolution was 480p as DeAOT.
  • Fully online inference. We passed all the modules frame by frame.

Pre-trained Models

Stages:

  • PRE: the pre-training stage with static images are the same as DeAOT.

  • PRE_YTB_DAV: the main-training stage with YouTube-VOS and DAVIS.

Model Param PRE PRE_YTB_DAV (LVOS eval checkpoints) PRE_YTB_DAV (LTV eval checkpoints) PRE_YTB_DAV (DAVIS eval checkpoints)
MAVOS 34M gdrive gdrive gdrive gdrive
R50-MAAVOS 41M gdrive gdrive gdrive gdrive
SwinB-MAVOS 91M gdrive gdrive gdrive gdrive

To use our pre-trained models to infer, a simple way is to set --model and --ckpt_path to your downloaded checkpoint's model type and file path when running eval.py.