8000 Probem of the result of test set that submitt on the KITTI benchmark · Issue #40 · hailanyi/TED · GitHub
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Feidashen1 opened this issue Feb 25, 2024 · 4 comments
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@Feidashen1
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Hello, your work is very meaningful, but when I reproduced this work, I verified that the results in the paper could be achieved on the validation set. However, after submitting the results of the test set on the Kitti platform, there was a significant gap between your results and yours.

What do you think are the possible problems? How can I achieve results similar to yours on the test set?

@Liu202209
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Hi, I would like to ask if you have reproduced the multi-modal results in the paper?Because my reproduction results were terrible:
bbox AP:98.9466, 90.4582, 89.9018
bev AP:90.1253, 88.8376, 80.2418
3d AP:89.7045, 87.3508, 79.3342
aos AP:98.53, 89.77, 88.96
Car AP_R40@0.70, 0.70, 0.70:
bbox AP:99.5549, 96.5883, 91.5515
bev AP:96.0639, 92.4806, 85.3564
3d AP:95.1403, 87.0011, 82.0037
aos AP:99.16, 95.74, 90.56
Car AP@0.70, 0.50, 0.50:
bbox AP:98.9466, 90.4582, 89.9018
bev AP:99.0606, 90.4330, 89.9194
3d AP:99.0323, 90.4258, 89.8929
aos AP:98.53, 89.77, 88.96
Car AP_R40@0.70, 0.50, 0.50:
bbox AP:99.5549, 96.5883, 91.5515
bev AP:99.5883, 96.5739, 91.5433
3d AP:99.5789, 96.5555, 91.5227
aos AP:99.16, 95.74, 90.56
which the score_threshold is 0.3. I have tried to set the score_threshold as 0.5, 0.7,which is worse.

@ty-zeck
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ty-zeck commented Dec 1, 2024

你好,想问一下你已经复现过论文中的多模态结果吗?因为我的复现结果很糟糕: bbox AP:98.9466, 90.4582, 89.9018 bev AP:90.1253, 88.8376, 80.2418 3d AP:89.7045, 87.3508, 79.3342 aos AP:98.53, 89.77, 88.96 汽车 AP_R40@0.70, 0.70, 0.70: bbox AP:99.5549, 96.5883, 91.5515 bev AP:96.0639, 92.4806, 85.3564 3d AP:95.1403, 87.0011, 82.0037 aos AP:99.16, 95.74, 90.56 汽车 AP@0.70, 0.50, 0.50: bbox AP:98.9466, 90.4582, 89.9018 bev AP:99.0606, 90.4330, 89.9194 3d AP:99.0323, 90.4258, 89.8929 aos AP:98.53, 89.77, 88.96 汽车 AP_R40@0.70, 0.50, 0.50: bbox AP:99.5549, 96.5883, 91.5515 bev AP:99.5883, 96.5739, 91.5433 3d AP:99.5789, 96.5555, 91.5227 aos AP:99.16, 95.74, 90.56 其中score_threshold 为0.3。我尝试将score_threshold设置为0.5、0.7,结果更糟糕。

我多模态的复现结果也很糟糕,而且epoch20-30评估的时候结果是很震荡的。

@Liu202209
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有一次的复现结果比较接近,但是还是差一些,差1%吧,主要是汽车中等类,当时的复现文件找不到了

@ty-zeck
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ty-zeck commented Dec 1, 2024

有一次的复现结果比较接近,但是还是差一些,差1%吧,主要是汽车中等类,当时的复现文件找不到了

同学,你是复现了很多次才得到一次接近的结果吗,我目前复现了两次,最高的也差好几个点,而且每个epoch的评估结果震荡很大。

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