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08/23/2023
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE
Building scalable vision-language models to learn from diverse, multimod...
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05/25/2023
ChatBridge: Bridging Modalities with Large Language Model as a Language Catalyst
Building general-purpose models that can perceive diverse real-world mod...
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05/22/2023
ConvBoost: Boosting ConvNets for Sensor-based Activity Recognition
Human activity recognition (HAR) is one of the core research themes in u...
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04/26/2023
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation
Medical image segmentation methods normally perform poorly when there is...
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02/14/2023
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Label efficiency has become an increasingly important objective in deep ...
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01/27/2023
A Strongly Polynomial-Time Algorithm for Weighted General Factors with Three Feasible Degrees
General factors are a generalization of matchings. Given a graph G with ...
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12/23/2022
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition
Human Activity Recognition (HAR) is one of the core research areas in mo...
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10/09/2022
MAMO: Masked Multimodal Modeling for Fine-Grained Vision-Language Representation Learning
Multimodal representation learning has shown promising improvements on v...
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05/06/2022
A Conformer-based Waveform-domain Neural Acoustic Echo Canceller Optimized for ASR Accuracy
Acoustic Echo Cancellation (AEC) is essential for accurate recognition o...
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04/05/2022
Birds of A Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentation
Unsupervised domain adaptation (UDA) aims to enhance the generalization ...
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03/15/2022
CSN: Component-Supervised Network for Few-Shot Classification
The few-shot classification (FSC) task has been a hot research topic in ...
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12/03/2021
SSDL: Self-Supervised Dictionary Learning
The label-embedded dictionary learning (DL) algorithms generate influent...
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12/01/2021
MDFM: Multi-Decision Fusing Model for Few-Shot Learning
In recent years, researchers pay growing attention to the few-shot learn...
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09/16/2021
MHFC: Multi-Head Feature Collaboration for Few-Shot Learning
Few-shot learning (FSL) aims to address the data-scarce problem. A stand...
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09/07/2021
CIM: Class-Irrelevant Mapping for Few-Shot Classification
Few-shot classification (FSC) is one of the most concerned hot issues in...
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12/20/2020
A Predictive Discrete-Continuum Multiscale Model of Plasticity With Quantified Uncertainty
Multiscale models of materials, consisting of upscaling discrete simulat...
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10/23/2020
DLDL: Dynamic Label Dictionary Learning via Hypergraph Regularization
For classification tasks, dictionary learning based methods have attract...
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10/23/2020
SAHDL: Sparse Attention Hypergraph Regularized Dictionary Learning
In recent years, the attention mechanism contributes significantly to hy...
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05/16/2020
A Dichotomy for Real Boolean Holant Problems
We prove a complexity dichotomy for Holant problems on the boolean domai...
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04/12/2020
From Holant to Quantum Entanglement and Back
Holant problems are intimately connected with quantum theory as tensor n...
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09/10/2019
Contraction: a Unified Perspective of Correlation Decay and Zero-Freeness of 2-Spin Systems
We study complex zeros of the partition function of 2-spin systems, view...
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04/17/2019
Class Specific or Shared? A Hybrid Dictionary Learning Network for Image Classification
Dictionary learning methods can be split into two categories: i) class s...
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04/04/2019
Complexity of Counting Weighted Eulerian Orientations with ARS
Unique prime factorization of integers is taught in every high school. W...
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03/07/2019
Label Embedded Dictionary Learning for Image Classification
Recently, label consistent k-svd(LC-KSVD) algorithm has been successfull...
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02/19/2019
WIDER Face and Pedestrian Challenge 2018: Methods and Results
This paper presents a review of the 2018 WIDER Challenge on Face and Ped...
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11/21/2018
Scene Text Detection with Supervised Pyramid Context Network
Scene text detection methods based on deep learning have achieved remark...
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04/30/2018
CrowdHuman: A Benchmark for Detecting Human in a Crowd
Human detection has witnessed impressive progress in recent years. Howev...
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11/21/2017
Repulsion Loss: Detecting Pedestrians in a Crowd
Detecting individual pedestrians in a crowd remains a challenging proble...
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12/02/2016