Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching
Authors: Stepan Tulyakov, Anton Ivanov, François Fleuret
NeurIPS 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We compare PDS to state-of-the-art methods published over the recent months, and demonstrate its superior performance on Flying Things3D and KITTI sets. |
| Researcher Affiliation | Academia | Stepan Tulyakov Space Engineering Center at École Polytechnique Fédérale de Lausanne stepan.tulyakov@epfl.ch Anton Ivanov Space Engineering Center at École Polytechnique Fédérale de Lausanne anton.ivanov@epfl.ch Francois Fleuret École Polytechnique Fédérale de Lausanne and Idiap Research Institute francois.fleuret@idiap.ch |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | We guarantee reproducibility of all experiments in this section by using only available data-sets, and making our code available online under open-source license after publication. |
| Open Datasets | Yes | We used three data-sets for our experiments: KITTI 12 [6] and KITTI 15 [22], that we combined into a KITTI set, and Flying Things3D [20] summarized in Table 3. |
| Dataset Splits | Yes | We make validation sets by withholding 500 images from the Flying Things3D training set, and 58 from the KITTI training set, respectively. |
| Hardware Specification | Yes | We also acknowledge the support of NVIDIA Corporation with the donation of the Ge Force GTX TITAN X used for this research. |
| Software Dependencies | No | Our experiments are done with the Py Torch framework [26]. |
| Experiment Setup | Yes | Table 2: Summary of training settings for every dataset. Flying Things3D KITTI Mode from scratch fine-tune Lr. schedule 0.01 for 120k, half every 20k 0.005 for 50k, half every 20k Iter. # 160k 100k Tr. image size 960 540 full-size 1164 330 Max disparity 255 255 Augmentation not used mix Up [42], anisotropic zoom, random crop |