Robust Depth Completion with Uncertainty-Driven Loss Functions
Authors: Yufan Zhu, Weisheng Dong, Leida Li, Jinjian Wu, Xin Li, Guangming Shi3626-3634
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our method has been tested on KITTI Depth Completion Benchmark and achieved the state-of-the-art robustness performance in terms of MAE, IMAE, and IRMSE metrics. |
| Researcher Affiliation | Academia | 1 School of Artificial Intelligence, Xidian University, Xi an 710071, China 2 Lane Dep. of CSEE, West Virginia University, Morgantown WV 26506, USA |
| Pseudocode | No | The paper describes network architectures and mathematical formulations but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an explicit statement about releasing source code or a link to a code repository for the described methodology. |
| Open Datasets | Yes | The KITTI depth completion benchmark(Uhrig et al. 2017) has 86898 Lidar frames for training, 1000 frames for validation, and 1000 frames for testing. |
| Dataset Splits | Yes | The KITTI depth completion benchmark(Uhrig et al. 2017) has 86898 Lidar frames for training, 1000 frames for validation, and 1000 frames for testing. |
| Hardware Specification | Yes | Our training is implemented by Pytorch with 5 NVIDIA GTX2080Ti GPUs and set batch-size to 5. |
| Software Dependencies | No | The paper mentions 'Pytorch' but does not provide specific version numbers for software dependencies. |
| Experiment Setup | Yes | Our training is implemented by Pytorch with 5 NVIDIA GTX2080Ti GPUs and set batch-size to 5. In our current implementation, we have used ADAM (Kingma and Ba 2014) as the optimization algorithm. We have set the learning rate to 1 10 4 when we train our multiscale joint prediction model and 2 10 4 when training uncertainty attention residual learning model. The other parameters are all the same with (β1, β2) = (0.9, 0.999), eps = 1 10 8 and Weight decay = 0. |