Revisiting 3D Object Detection From an Egocentric Perspective
Authors: Boyang Deng, Charles R Qi, Mahyar Najibi, Thomas Funkhouser, Yin Zhou, Dragomir Anguelov
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments on the large-scale Waymo Open Dataset show that SDE better reflects the impact of detection quality on the ego-agent s safety compared to Io U; and the estimated contours from Star Poly consistently improve the egocentric detection quality over recent 3D object detectors. |
| Researcher Affiliation | Industry | Boyang Deng Charles R. Qi Mahyar Najibi Thomas Funkhouser Yin Zhou Dragomir Anguelov Waymo LLC Google Research |
| Pseudocode | No | The paper does not contain any clearly labeled 'Pseudocode' or 'Algorithm' blocks, nor does it present structured steps in a code-like format. |
| Open Source Code | No | The code and the data are proprietary. We plan to release the code of computing the metrics upon acceptance. |
| Open Datasets | Yes | All analysis is based on the Waymo Open Dataset [53] validation set. |
| Dataset Splits | Yes | All analysis is based on the Waymo Open Dataset [53] validation set. |
| Hardware Specification | Yes | We include this information in the supplementary material for our proposed Star Poly model. |
| Software Dependencies | No | The paper mentions using a 'Point Net [40] model' and 'Adam' optimizer but does not specify version numbers for any software dependencies or libraries required for reproduction. |
| Experiment Setup | Yes | We use a resolution n = 256 for all following experiments. ( d1, ..., dn) is uniformly sampled from the boundary of a square. During training, γ and β are both set to 0.1, which is determined by a grid search over the hyperparameters. Please refer to the supplementary material for more model details. |