Research
SPair-71k: A Large-scale Benchmark for Semantic Correspondence
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Hyperpixel Flow:
Semantic Correspondence with Multi-layer Neural Features
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Relational Knowledge Distillation
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Attentive Semantic Alignment with Offset-Aware Correlation Kernels
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Visual Reference Resolution using Attention Memory for Visual Dialog
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MarioQA: Answering Questions by Watching Gameplay Videos
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Weakly Supervised Semantic Segmentation using Web-Crawled Videos
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Superpixel-based Tracking-by-Segmentation using Markov Chains
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Text-guided Attention Model for Image Captioning
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Training Recurrent Answering Units with Joint Loss Minimization for VQA
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Superpixel segmentation by constrained minimax label propagation
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TransferNet: Transfer learning for semantic segmentation
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MDNet for visual tracking "VOT2015 Winner"
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DPPnet for image question answering
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Unsupervised Co-activity Detection from Multiple Videos using Absorbing Markov Chain
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DecoupledNet for semi-supervised semantic segmentation
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DeconvNet for semantic segmentation
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Tracking-by-segmentation using online GBDT
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Online tracking by learning discriminative saliency map with CNN
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Beyond chain models for visual tracking: A Trilogy
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Event detection
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Joint human segmentation and pose tracking
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Tracking with occlusion reasoning
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Generalized background subtraction
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Fast nearest neighbor search
국가
대한민국
소속기관
포항공과대학교 (학교)
연락처
054-279-2385 http://cvlab.postech.ac.kr/lab/
책임자
조민수 mscho@postech.ac.kr