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Recurrent Exposure Generation for Low-Light Face Detection
Face detection from low-light images is challenging due to limited photo...
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Deep Bilateral Retinex for Low-Light Image Enhancement
Low-light images, i.e. the images captured in low-light conditions, suff...
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STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition
Effective and Efficient spatio-temporal modeling is essential for action...
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Weakly-Supervised Multi-Level Attentional Reconstruction Network for Grounding Textual Queries in Videos
The task of temporally grounding textual queries in videos is to localiz...
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Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
Cancer diagnosis, prognosis and therapeutic response predictions are bas...
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Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
Temporal sentence grounding in videos aims to detect and localize one ta...
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Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks
Histology-based grade classification is clinically important for many ca...
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Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Coding
Convolutional neural networks can be trained to perform histology slide ...
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Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction
The task of temporally grounding language queries in videos is to tempor...
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Controllable Video Captioning with POS Sequence Guidance Based on Gated Fusion Network
In this paper, we propose to guide the video caption generation with Par...
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An alarm prediction framework for financial IT system using hybrid machine learning methods
Informatization grows rapidly in all walks of life, going with the enhan...
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Non-local NetVLAD Encoding for Video Classification
This paper describes our solution for the 2^nd YouTube-8M video understa...
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Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning
Dense video captioning is a newly emerging task that aims at both locali...
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