Comments (3)
The set of shortest paths are available here: https://github.com/facebookresearch/EmbodiedQA#download-and-preprocess-the-dataset, and for evaluation, we spawn the agent 10, 30, 50 actions away from the target along these shortest paths: https://github.com/facebookresearch/EmbodiedQA/blob/master/training/train_nav.py#L102
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Got it. Thanks.
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Would it be possible for you to provide starting coordinates for each question for reproducibility?
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Related Issues (20)
- Will you be able to provide trained models?
- TypeError: local_create_house() takes 2 positional arguments but 3 were given HOT 2
- train_nav.py goes into Pdb.set_trace() HOT 2
- train_vqa (and others) hanging when using multiprocessing
- Out of memory in train_vqa.py HOT 4
- Errors when running train_nav.py HOT 4
- Errors running train_eqa.py HOT 1
- build_graph() in house3d.py takes a lot of memory HOT 1
- suncg data unavailable HOT 9
- A question about VQA part
- Pretraining MultitaskCNN
- no 'torch.save(checkpoint, checkpoint_path)' HOT 9
- About how to keep "d_0_10,30,50" the same distance length all the times?
- Clarify eval/train parallel runs in vqa, nav, and eqa main HOT 3
- Assertion failure when running vanilla train_nav.py HOT 9
- Out of memory in train_vqa.py with 8 num_processes HOT 1
- load_graph() returns empty graph HOT 2
- The version of SUNCG dataset v1, v2 or v2.1 HOT 1
- Supply new results on the provided dataset
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