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你好,周博士。我在搭建的模型中考虑了未来轨迹的交互,训练损失和您QCNeXt模型相似。但我的模型存在的问题在于轨迹细化模块的输出轨迹的偏移在训练过程中很快趋于0值,这也导致Lpropose和Lrefine的值在训练过程中相同,轨迹细化模块失去了存在的意义。请问您在探索过程中出现过类似的情况吗?
The text was updated successfully, but these errors were encountered:
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你好,周博士。我在搭建的模型中考虑了未来轨迹的交互,训练损失和您QCNeXt模型相似。但我的模型存在的问题在于轨迹细化模块的输出轨迹的偏移在训练过程中很快趋于0值,这也导致Lpropose和Lrefine的值在训练过程中相同,轨迹细化模块失去了存在的意义。请问您在探索过程中出现过类似的情况吗?
The text was updated successfully, but these errors were encountered: