exiawsh

> The data generated is structured as follows: > > ``` > - SAVE_PATH: provided in run_evaluation.sh > - {routes_file_name}_{timestamp}: contains data for an individual route > - rgb_{front, left,...

> Yes, the structure is correct. Here you used `eval_routes_weathers.xml` as the ROUTES variable in run_evaluation.sh. To generate the towns in our training dataset, you would need to use the...

> Yes, the structure is correct. Here you used `eval_routes_weathers.xml` as the ROUTES variable in run_evaluation.sh. To generate the towns in our training dataset, you would need to use the...

In fact, I pay more attention to the semantic segmentation process of BEV by using implicit neural representation, so I want to use data for debugging quickly... I'm sorry to...

I have solved the above problems. It seems that I should restart terminal, when change the var.

> If you want to quickly access some data, we have released the dataset for TransFuser here: https://github.com/autonomousvision/transfuser#dataset > > See the readme in that repository for more details. The...

> The main difference is the weathers (in TransFuser, we use 14 fixed weathers, and in NEAT, we randomly sample the weather parameters from Gaussian distributions). There are also minor...

Hello, I also conducted research on PETRV2. Here are some of my understandings： （1）There are no explicit time positional embedding, so they regression the position offset instead. （2）The way to...

Hello, the temporal fusion in PETRv2 is mainly processed in an offline manner: https://github.com/megvii-research/PETR/blob/e48faec8aa24bdd14f95692428ddc4982f2f71cb/tools/generate_sweep_pkl.py#L53 Recently, we have another version of temporal fusion for PETR, named StreamPETR, which performs better than...

> @exiawsh Hi ， would you like to explain more detail? In PETRV2, the loaded data camera=12, after backbone processing, is equivalent to the 2d feature map concat of the...