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gongjy 2024-10-05 09:48:58 +08:00
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README.md
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@ -511,7 +511,7 @@ python web_server.py
- 值得改进的方面：
- 更简单的Projection的跨模态特征对齐方式，相较于Cross-Attention会带来更大的性能损失。
- Clip模型可以尝试更大性能更强的large系列，用更具细粒度的token表征图像特征，目前仍非常粗糙。
- 分辨率不高，理论上只有224*224（minimind-v数据集为节省空间，仅设定为128*128）。
- 分辨率不高，理论上只有224×224（minimind-v数据集为节省空间，仅设定为128×128）。
- ...
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README_en.md
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@ -497,7 +497,7 @@ Based on the provided table data, the performance of the four models can be summ
- Areas for improvement:
- Simpler projection methods for cross-modal feature alignment result in greater performance loss compared to Cross-Attention.
- Larger and more powerful large-series Clip models can be tried, using more fine-grained token representations for image features, which are currently very rough.
- The resolution is not high, theoretically only 224*224 (minimind-v dataset is set to 128*128 to save space).
- The resolution is not high, theoretically only 224×224 (minimind-v dataset is set to 128×128 to save space).
- ...
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