Comments (2)
daizuozhuo
commented on May 18, 2024
有一些差异很正常，很可能系统里面还有别的随机部分没有考虑到。
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tangsipeng
commented on May 18, 2024
CUDA_VISIBLE_DEVICES=0,1 python examples/cluster_contrast_train_usl.py -b 256 -a resnet50 -d market1501 --iters 200 --momentum 0.1 --eps 0.4 --num-instances 16
Mean AP: 79.6%
CMC Scores:
top-1 90.3%
top-5 95.5%
top-10 97.0%
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Related Issues (20)
- Can't reproduce MSMT17 results HOT 8
- 关于Memory Initialization的一点问题 HOT 4
- Why is the performance of the model trained with multi GPUs much better than that of the model trained with single GPU in this method? HOT 5
- 关于use hard的问题 HOT 4
- I downloaded the trained model you released, but only market and Dukle. Can you publish the model trained on VeRi? HOT 1
- PersonX 数据集上mAP只有36.0左右 HOT 6
- why don't use pseudo_labeled=-1 ?
- Why hard sampling is only beneficial for resnet_ibn_a?
- Why the result cannot be reproduced? HOT 2
- Different methods in memory update
- About the setting of batch_size and iter number HOT 1
- 为啥msmt17的指标sota都只有20多呢？ HOT 1
- Warning: Leaking Caffe2 thread-pool after fork.
- Can't reproduce the result of MTMC17 to 33.3 using avg pooling HOT 2
- dataset HOT 4
- Why this paper is not accepted... HOT 1
- 运行问题 HOT 1
- cm模块中的backward代码好像没有起作用 HOT 2
- 在使用nocam sampler 的情况下，batchsize越大结果反而越低
- 关于不能复现msmt17相关指标的问题 HOT 1
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