input stringlengths 14 315 | answer stringlengths 9 2.16k | gold_ctxs listlengths 1 15 | ctxs listlengths 11 186 |
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What are the side effects of group convolution?
| The side effects of group convolutions are: blocked flow of information between channel groups when multiple group convolutions are combined; and damaged individual convolution filters for each group due to decreased number of input channels [16]. | [
16
] | [
{
"id": "1707.01083_all_0",
"text": " Building deeper and larger convolutional neural networks (CNNs) is a primary trend for solving major visual recognition tasks (21, 9, 33, 5, 28, 24). The most accurate CNNs usually have hundreds of layers and thousands of channels (9, 34, 32, 40), thus requiring computa... |
How does normalizing the features and weights in the softmax loss function improve the performance of deep face recognition systems? | Normalizing the weights only can help angular/cosine-margin-based loss to make the learned features more discriminative, whereas normalizing only the learned features can help overcome the bias to the sample distribution of the softmax [25]. Since L2-norms of learned features with softmax loss were observed to be reflective of the quality of the face, making all the features have the same L2-norm may help to give similar attention to all different qualities of samples [26]. | [
25,
26
] | [
{
"id": "1804.06655_all_0",
"text": " Face recognition (FR) has been the prominent biometric technique for identity authentication and has been widely used in many areas, such as military, finance, public security and daily life. FR has been a long-standing research topic in the CVPR community. In the early... |
If, for a certain model, it was theorized that the penultimate layer is the most important later for generating embeddings, how could discriminative fine-tuning be used to validate or refute that theory? | In this work, discriminative fine-tuning was used to fine-tune each layer with a different learning rate [17]. Specifically, the learning rate was decreased going from the last layer to lower layers [45]. The authors found that this improved performance across several datasets [19]. | [
17,
45,
19
] | [
{
"id": "1801.06146_all_0",
"text": " Inductive transfer learning has had a large impact on computer vision (CV). Applied CV models (including object detection, classification, and segmentation) are rarely trained from scratch, but instead are fine-tuned from models that have been pretrained on ImageNet, MS... |
Why should LSTM based auto-encoder models learn good features? | "Since LSTM based auto-encoder models control the learning an identity mapping, it forced learn good(...TRUNCATED) | [
14
] | [{"id":"1502.04681_all_0","text":" Understanding temporal sequences is important for solving many pr(...TRUNCATED) |
"Can the the NetVLAD pooling layer be inserted into any other CNN or does it support certain archite(...TRUNCATED) | Yes, it is a generic building block and can be inserted into any other CNN architectures [48]. | [
48
] | [{"id":"1511.07247_all_0","text":" Visual place recognition has received a significant amount of att(...TRUNCATED) |
"Why does author experiment the quantized linear supernet design even though Radosavovic et al. alre(...TRUNCATED) | "The previous study shows the linear design is beneficial in terms of computational complexity, whil(...TRUNCATED) | [
34
] | [{"id":"2009.02009_all_0","text":" As there are growing needs of deep learning applications based on(...TRUNCATED) |
"Why did the dot scoring function perform well for global attention while the general scoring functi(...TRUNCATED) | "Authors thinks it's interesting to observe that \"dot\" works well for the global attention and \"g(...TRUNCATED) | [
38
] | [{"id":"1508.04025_all_0","text":" Neural Machine Translation (NMT) achieved state-of-the-art perfor(...TRUNCATED) |
Is it true that the first-order approximation led to roughly 33% speed-up in network computation? | "According to the paper, eliminating the Hessian calculation increases the overall calculation speed(...TRUNCATED) | [
31
] | [{"id":"1703.03400_all_0","text":" Learning quickly is a hallmark of human intelligence, whether it (...TRUNCATED) |
"Why didn't the authors intend a \"chord\" to represent a more meaningful unit in music, such as a b(...TRUNCATED) | "The authors intend a \"chord\" to represent simultaneous notes to intuitively models a polyphonic s(...TRUNCATED) | [
5,
6
] | [{"id":"2208.14867_all_0","text":" Computational modeling of expressive music performance focuses on(...TRUNCATED) |
Who collected the queries from MSMARCO-Passage dataset to make MSMARCO-TRAIN query set? | "MARCO-Passage collection is a large-scale publicly available corpus and two query sets derived from(...TRUNCATED) | [
40
] | [{"id":"2204.11673_all_0","text":" Passage Re-ranking is a crucial stage in modern information retri(...TRUNCATED) |
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