Hi, thanks for your great work!
In the paper，VISTA projects the input feature sequences X1 ∈ Rn×df and X2 ∈ Rm×df into
queries Q ∈ Rn×dq and keys K ∈ Rm×dq (values V ∈Rm×dv) via convolutional operators of 3 × 3 kernels, where
dq and dv are the feature dimensions of queries (keys) and values. To decouple the classification and regression tasks,
Q and K are further projected into Qi, Ki, i ∈ {sem, geo} via individual MLP (implemented as 1D convolution).
However，This is not the case in the code！
Hi, thanks for your great work!
In the paper，VISTA projects the input feature sequences X1 ∈ Rn×df and X2 ∈ Rm×df into
queries Q ∈ Rn×dq and keys K ∈ Rm×dq (values V ∈Rm×dv) via convolutional operators of 3 × 3 kernels, where
dq and dv are the feature dimensions of queries (keys) and values. To decouple the classification and regression tasks,
Q and K are further projected into Qi, Ki, i ∈ {sem, geo} via individual MLP (implemented as 1D convolution).
However，This is not the case in the code！