A Pytorch Implementation for Compact Bilinear Pooling.

Last update: Dec 23, 2022

Overview

CompactBilinearPooling-Pytorch

A Pytorch Implementation for Compact Bilinear Pooling. Adapted from tensorflow_compact_bilinear_pooling

Prerequisites

pip install pytorch_fft

Usage

from torch import nn
from torch.autograd import Variable
from CompactBilinearPooling import CompactBilinearPooling

bottom1 = Variable(torch.randn(128, 512, 14, 14)).cuda()
bottom2 = Variable(torch.randn(128, 512, 14, 14)).cuda()

layer = CompactBilinearPooling(512, 512, 8000)
layer.cuda()
layer.train()

out = layer(bottom1, bottom2)

Reference

Yang Gao, et al. "Compact Bilinear Pooling." in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2016).
Akira Fukui, et al. "Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding." arXiv preprint arXiv:1606.01847 (2016).

Owner

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A Pytorch Implementation for Compact Bilinear Pooling.

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A Pytorch Implementation for Compact Bilinear Pooling.

Related tags

Overview

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Prerequisites

Usage

Reference

Owner

[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

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