Cryptocurrency, Bitcoin, and Behind Dark Web Technology
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Real-ESRGAN: Training Real-World Blind Super-Resolution
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Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data Though many attempts have been made in blind superresolution to restore ...

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Filters for Specific Degradations in Blind Super-Resolution
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Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution Recent blind super-resolution (SR) methods typically consist of two ...

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Dynamic Token Normalization improves Vision Transformers
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Dynamic Token Normalization improves Vision Transformers Vision Transformer (ViT) and its variants (eg, Swin, PVT) have achieved great success in various ...

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Uncertainty Modeling for Out-of-Distribution Generalization
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Uncertainty Modeling for Out-of-Distribution Generalization Though remarkable progress has been achieved in various vision tasks, deep neural networks still ...

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Audio-to-symbolic Arrangement via Cross-modal Music
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Audio-to-symbolic Arrangement via Cross-modal Music Representation Learning Could we automatically derive the score of a piano accommodation based on the ...

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Hot-Refresh Model Upgrades with Regression-Free Compatible Training
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Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval The task of hot-refresh model upgrades of image retrieval systems plays ...

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Unified Multi-modal Transformers for Joint Video Moment Retrieval
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Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection Finding relevant moments and highlights in videos according to ...

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A Bi-lingual Benchmark for Text Segmentation in the Wild
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A Bi-lingual Benchmark for Text Segmentation in the Wild As a prerequisite of many text-related tasks such as text erasing and text style transfer, text ...

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Object-aware Video-language Pre-training for Retrieval
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Object-aware Video-language Pre-training for Retrieval Recently, by introducing large-scale dataset and strong transformer network, video-language ...

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Bridging Video-text Retrieval with Multiple Choice Questions
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Bridging Video-text Retrieval with Multiple Choice Questions Pre-training a model to learn transferable video-text representation for retrieval has attracted ...

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Active Learning for Open-set Annotation
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Active Learning for Open-set Annotation Existing active learning studies typically work in the closed-set setting by assuming that all data examples to be ...

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Temporally Efficient Vision Transformer for Video Instance Segmentation
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Temporally Efficient Vision Transformer for Video Instance Segmentation Recently vision transformer has achieved tremendous success on image-level visual ...

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 Universal Backward-Compatible Representation Learning
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 Universal Backward-Compatible Representation Learning Conventional model upgrades for visual search systems require offline refresh of gallery features by ...

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A Hierarchical Speaker Representation Framework
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A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion Typically, singing voice conversion (SVC) depends on an embedding ...

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PC-Dance: Posture-controllable Music-driven Dance Synthesis
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PC-Dance: Posture-controllable Music-driven Dance Synthesis Music-driven dance synthesis is a task to generate high-quality dance according to the music given ...

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RepSR: Training Efficient VGG-style Super-Resolution Networks
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RepSR: Training Efficient VGG-style Super-Resolution Networks with Structural Re-Parameterization and Batch Normalization This paper explores training ...

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MM-RealSR: Metric Learning based Interactive Modulation
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MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution Interactive image restoration aims to restore images by adjusting ...

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VQFR: Blind Face Restoration with Vector-Quantized
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VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder Although generative facial prior and geometric prior have recently ...

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Predicting Model Transferability in a Self-challenging Fisher Space
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Predicting Model Transferability in a Self-challenging Fisher Space This paper addresses an important problem of ranking the pre-trained deep neural networks ...

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mc-BEiT: Multi-choice Discretization for Image BERT Pre-training
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mc-BEiT: Multi-choice Discretization for Image BERT Pre-training Image BERT pre-training with masked image modeling (MIM) becomes a popular practice to cope ...

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