Create README.md

README.md

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+---
+license: apache-2.0
+size_categories:
+- 1K<n<10K
+---
+# Image as an IMU: Real-world Finetuning Dataset
+
+Official real-world finetuning dataset from *Image as an IMU: Estimating Camera Motion from a Single Motion-Blurred Image* (ICCV 2025 Oral).
+
+[[arXiv](https://arxiv.org/abs/2503.17358)] [[Webpage](https://jerredchen.github.io/image-as-imu/)] [[GitHub](https://github.com/jerredchen/image-as-an-imu)]
+
+**[PIXL, University of Oxford](https://pixl.cs.ox.ac.uk/)**
+
+[Jerred Chen](https://jerredchen.github.io/), [Ronald Clark](https://ronnie-clark.co.uk/)
+
+---
+
+## Dataset Details
+
+This dataset consists of 32 sequences of real-world motion-blurred videos in various indoor scenes, captured using the iPhone 13 camera.
+
+`dataset_train_real-world.csv` and `dataset_val_real-world.csv` are the CSV files used for training/validating the model in the paper. These can be directly plugged into the provided dataloader in the GitHub.
+
+The CSVs provide the following:
+- blurred: the relative path to the (resized 320x224) motion-blurred RGB image
+- ts1,ts2: the frame timestamps between the previous RGB and next RGB image
+- fx,fy,cx,cy: the *scaled* camera intrinsics, corresponding to the 320x224 image
+- bRa_qx,bRa_qy,bRa_qz,bRa_qw: body-frame rotational velocity, parameterized as a quaternion
+- bta_x,bta_y,bta_z: body-frame translational velocity
+- exposure: exposure time at the given image
+- sequence: the sequence name
+
+## Sequence Details
+
+Each sequence consists of the following:
+```
+sequence1/
+├─ blurry_frames_320x224
+│  ├─ XXXXXX.jpg
+│  └─ ...
+├─ confidence
+│  ├─ XXXXXX.png
+│  └─ ...
+├─ depth
+│  ├─ XXXXXX.png
+│  └─ ...
+├─ rgb
+│  ├─ XXXXXX.jpg
+│  └─ ...
+├─ rgb_320x224
+│  ├─ XXXXXX.jpg
+│  └─ ...
+└─ blurred_frames_320x224.csv
+└─ camera_matrix.csv
+└─ camera_matrix_320x224.csv
+└─ imu.csv
+└─ odometry.csv
+└─ velocities.csv
+```
+
+Sequences were recorded using the [StrayScanner app](https://apps.apple.com/us/app/stray-scanner/id1557051662), slightly modified to also obtain the exposure time from ARKit.
+`confidence`, `depth`, `rgb`, `camera_matrix.csv`, `imu.csv`, and `odometry.csv` are the original outputs from StrayScanner.
+
+We provide the following data in addition to the StrayScanner outputs:
+- `rgb_320x224` are the resized recorded RGB images
+- `blurry_frames_320x224` are the identified frames with more extensive blur using FFT as described in [Liu et al.](https://ieeexplore.ieee.org/document/4587465)
+- `camera_matrix_320x224.csv` are the corresponding scaled camera intrinsics
+- `velocities.csv` consist of the translational velocities computed from ARKit poses in `odometry.csv` and the rotational velocities directly from the gyroscope. 
+
+Of course, the RGB images/camera intrinsics can be resized/scaled online during training; we provide this to maintain consistency with our own training.
+
+Since the ARKit computed poses can have very large errors, `dataset_train_real-world.csv` consists of manually filtered samples without large outlier pose estimates.