Qiankun Liu
Qiankun Liu
Hi, thanks for your great works! I found that `prev_query_embed` of track query in `deformable_transformer.py` https://github.com/timmeinhardt/trackformer/blob/df70fef0539dc6ebe8ed26bf1ce55dd6e8f87968/src/trackformer/models/deformable_transformer.py#L214 is set to zeros. However, the `query_embed` of detection query is learned end-to-end, which...
Hi Yifu, Thanks for your great work. Here I have an issue about the results in Table 7 (in the newer version paper). The first row shows the results when...
Hi @timmeinhardt , thanks for your great work! After checking the code, I found that (1) the number of clases is set to 20 even only the person is tracked;...
Hi @FengLi-ust , thanks for your great works! In the appendix, you stated that `We also follow [17, 5, 4] to use point loss in mask loss for efficiency`. There...
Hi @tianweiy, thanks for the great works! I have followed the instructions to install some dependencies. Everything seems OK. But: 1) When I try to run: ` python tools/dist_test.py configs/nusc/voxelnet/nusc_centerpoint_voxelnet_0075voxel_fix_bn_z.py...
Hi @LTH14 , Great work! Here I have a question about the computation of logits after decoder. I find that a MlmLayer is used. The output of decoder is mapped...
I write a simple test code `code 1` as follows. I first generate a 3D ndarray randomly, and add a new dimensionality to represente the batch_size dimension. The box is...
There is an error: idx = torch.LongTensor([A.tocoo().row, A.tocoo().col]) RuntimeError: sizes must be non-negative in the following function. ``` def get_torch_sparse_matrix(A, dev): ''' A : list of sparse adjacency matrices '''...