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09/10/2023
Towards Fully Decoupled End-to-End Person Search
End-to-end person search aims to jointly detect and re-identify a target...
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07/18/2023
Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis
This paper presents ER-NeRF, a novel conditional Neural Radiance Fields ...
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09/22/2020
Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss
Person Re-IDentification (ReID) aims at re-identifying persons from diff...
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09/16/2020
Information Bottleneck Constrained Latent Bidirectional Embedding for Zero-Shot Learning
Zero-shot learning (ZSL) aims to recognize novel classes by transferring...
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08/04/2020
Select, Extract and Generate: Neural Keyphrase Generation with Syntactic Guidance
In recent years, deep neural sequence-to-sequence framework has demonstr...
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05/19/2020
Addressing Class-Imbalance Problem in Personalized Ranking
Pairwise ranking models have been widely used to address recommendation ...
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03/31/2020
Binary Neural Networks: A Survey
The binary neural network, largely saving the storage and computation, s...
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03/15/2020
Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection
Video anomaly detection is of critical practical importance to a variety...
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11/20/2019
Unified Multifaceted Feature Learning for Person Re-Identification
Person re-identification (ReID) aims at re-identifying persons from diff...
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09/09/2019
Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching
State-of-the-art deep learning based stereo matching approaches treat di...
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06/18/2019
A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks
Acceleration of convolutional neural network has received increasing att...
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03/28/2018
Deeply Supervised Semantic Model for Click-Through Rate Prediction in Sponsored Search
In sponsored search it is critical to match ads that are relevant to a q...
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03/15/2018
Exploring Linear Relationship in Feature Map Subspace for ConvNets Compression
While the research on convolutional neural networks (CNNs) is progressin...
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03/15/2018
Fast Subspace Clustering Based on the Kronecker Product
Subspace clustering is a useful technique for many computer vision appli...
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07/07/2017
