fatal factors that make the self-supervised training for monodepth estimation extremely difficult when trained on nuScenes Human: I've been working on monodepth estimation in a self-supervised manner and have referred to monodepth2. While training on nuScene, I found it hard to train the model for some reason. What would be fatal factors for the sucessful training? ChatGPT: Training a self-supervised monodepth model like Monodepth2 on a complex dataset like nuScenes can be tricky. Here are some fatal factors that co.. 더보기 Noise estimation idea 2 Human: Assume we want to OGMs for 2 classes, which results in {X_1, X_2}. When estimating the intrinsic noise in X1, I think I can take advantage of X_2 as a prior information. What would be a common practice? ChatGPT: Leveraging X2X_2X2 as Prior Information for Noise Estimation in X1X_1X1Since you are estimating the intrinsic noise in X1X_1X1, it makes sense to use X2X_2X2 as prior informat.. 더보기 Improving DDPD noise estimation ChatGPT: To improve the performance of your U-Net-based intrinsic noise estimation network, consider the following architectural modifications: 1. Enhancing Feature Representationsa. Using Residual Connections (ResUNet)Replace standard convolutional blocks with Residual Blocks to ease gradient flow and improve training stability.Residual blocks reduce vanishing gradient issues, helping the netwo.. 더보기 이전 1 2 3 4 5 ··· 69 다음