diff --git a/README.md b/README.md
index 779571acb..185948a87 100644
--- a/README.md
+++ b/README.md
@@ -159,7 +159,7 @@ Selected supported methods are shown in the below table. The results are the 3D
 | [Voxel R-CNN (Car)](tools/cfgs/kitti_models/voxel_rcnn_car.yaml) | ~2.2 hours| 84.54 | - | - | [model-28M](https://drive.google.com/file/d/19_jiAeGLz7V0wNjSJw4cKmMjdm5EW5By/view?usp=sharing) |
 | [Focals Conv - F](tools/cfgs/kitti_models/voxel_rcnn_car_focal_multimodal.yaml) | ~4 hours| 85.66 | - | - | [model-30M](https://drive.google.com/file/d/1u2Vcg7gZPOI-EqrHy7_6fqaibvRt2IjQ/view?usp=sharing) |
 ||
-| [CaDDN (Mono)](tools/cfgs/kitti_models/CaDDN.yaml) |~15 hours| 21.38 | 13.02 | 9.76 | [model-774M](https://drive.google.com/file/d/1OQTO2PtXT8GGr35W9m2GZGuqgb6fyU1V/view?usp=sharing) |
+| [CaDDN (Mono)](tools/cfgs/kitti_models/CaDDN.yaml) |~15 hours| 21.38 | 13.02 | 9.76 | [model-774M](https://www.icloud.com/iclouddrive/035Sje2eSDpnQv20kk74bNE_A#caddn%5Fpcdet) |
 
 ### Waymo Open Dataset Baselines
 We provide the setting of [`DATA_CONFIG.SAMPLED_INTERVAL`](tools/cfgs/dataset_configs/waymo_dataset.yaml) on the Waymo Open Dataset (WOD) to subsample partial samples for training and evaluation, 
diff --git a/docs/GETTING_STARTED.md b/docs/GETTING_STARTED.md
index 9bc558da9..c473d4f3a 100644
--- a/docs/GETTING_STARTED.md
+++ b/docs/GETTING_STARTED.md
@@ -9,7 +9,7 @@ Currently we provide the dataloader of KITTI, NuScenes, Waymo, Lyft and Pandaset
 
 ### KITTI Dataset
 * Please download the official [KITTI 3D object detection](http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) dataset and organize the downloaded files as follows (the road planes could be downloaded from [[road plane]](https://drive.google.com/file/d/1d5mq0RXRnvHPVeKx6Q612z0YRO1t2wAp/view?usp=sharing), which are optional for data augmentation in the training):
-* If you would like to train [CaDDN](../tools/cfgs/kitti_models/CaDDN.yaml), download the precomputed [depth maps](https://drive.google.com/file/d/1qFZux7KC_gJ0UHEg-qGJKqteE9Ivojin/view?usp=sharing) for the KITTI training set
+* If you would like to train [CaDDN](../tools/cfgs/kitti_models/CaDDN.yaml), download the precomputed [depth maps](https://www.icloud.com/iclouddrive/0fdSov6vL7HINa6S6x0ZKxKUg#depth%5F2) for the KITTI training set
 * NOTE: if you already have the data infos from `pcdet v0.1`, you can choose to use the old infos and set the DATABASE_WITH_FAKELIDAR option in tools/cfgs/dataset_configs/kitti_dataset.yaml as True. The second choice is that you can create the infos and gt database again and leave the config unchanged.
 
 ```