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Found 15 papers, 2 papers with code
Image Comes Dancing with Collaborative Parsing-Flow Video Synthesis
The integration of human parsing and appearance flow effectively guides the generation of video frames with realistic appearance.
Probabilistic Human-like Gesture Synthesis from Speech using GRU-based WGAN
The motions synthesized by the proposed system are evaluated via an objective measure and a subjective experiment, showing that the proposed model outperforms a baseline model which is trained by a state-of-the-art GAN-based algorithm, using the same dataset.
EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning
Many algorithms try to predict model performance of the pruned sub-nets by introducing various evaluation methods.
Ranked #6 on
Network Pruning
on ImageNet
Towards Non-task-specific Distillation of BERT via Sentence Representation Approximation
There are plenty of studies showing that the knowledge distillation is efficient in transferring the knowledge from BERT into the model with a smaller size of parameters.
Guiding Variational Response Generator to Exploit Persona
Leveraging persona information of users in Neural Response Generators (NRG) to perform personalized conversations has been considered as an attractive and important topic in the research of conversational agents over the past few years.
Improving the Robustness of Deep Reading Comprehension Models by Leveraging Syntax Prior
Despite the remarkable progress on Machine Reading Comprehension (MRC) with the help of open-source datasets, recent studies indicate that most of the current MRC systems unfortunately suffer from weak robustness against adversarial samples.
MemeFaceGenerator: Adversarial Synthesis of Chinese Meme-face from Natural Sentences
Chinese meme-face is a special kind of internet subculture widely spread in Chinese Social Community Networks.
Fashion Editing with Adversarial Parsing Learning
Interactive fashion image manipulation, which enables users to edit images with sketches and color strokes, is an interesting research problem with great application value.
Learning to Generate Structured Queries from Natural Language with Indirect Supervision
Generating structured query language (SQL) from natural language is an emerging research topic.
Why Do Neural Response Generation Models Prefer Universal Replies?
Recent advances in sequence-to-sequence learning reveal a purely data-driven approach to the response generation task.
A Prospective-Performance Network to Alleviate Myopia in Beam Search for Response Generation
Generative dialog models usually adopt beam search as the inference method to generate responses.
LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics
The experimental results have shown that our proposed corpus can be taken as a new benchmark dataset for the NRG task, and the presented metrics are promising to guide the optimization of NRG models by quantifying the diversity of the generated responses reasonably.
Scalable Angular Discriminative Deep Metric Learning for Face Recognition
To bridge the gap, we impose the intra-class cosine similarity between the features and weight vectors in softmax loss larger than a margin in the training step, and extend it from four aspects.
Exponential Discriminative Metric Embedding in Deep Learning
With the remarkable success achieved by the Convolutional Neural Networks (CNNs) in object recognition recently, deep learning is being widely used in the computer vision community.
Ranking Responses Oriented to Conversational Relevance in Chat-bots
For automatic chatting systems, it is indeed a great challenge to reply the given query considering the conversation history, rather than based on the query only.
