Seminar 2023
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A2FSeg: Adaptive Multi-Modal Fusion Network for Medical Image Segmentation
A2FSeg: Adaptive Multi-Modal Fusion Network for Medical Image Segmentation
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CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
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Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
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You Don't Have to Be Perfect to Be Amazing: Unveil the Utility of Synthetic Images
You Don't Have to Be Perfect to Be Amazing: Unveil the Utility of Synthetic Images
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BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
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Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation
Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation
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EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation
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RepVGG: Making VGG-style ConvNets Great Again
RepVGG: Making VGG-style ConvNets Great Again
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Simple Online and Realtime Tracking with a Deep Association Metric
Simple Online and Realtime Tracking with a Deep Association Metric
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WaveNet: A Generative Model for Raw Audio
WaveNet: A Generative Model for Raw Audio
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LoRA: Low-Rank Adaptation of Large Language Models
LoRA: Low-Rank Adaptation of Large Language Models
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Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
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High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions
High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions
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Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification
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STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection
STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection
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Deep Region and Multi-label Learning for Facial Action Unit Detection
Deep Region and Multi-label Learning for Facial Action Unit Detection
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Multimodal Few-Shot Learning with Frozen Language Models
Multimodal Few-Shot Learning with Frozen Language Models
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Communication-Efficient Learning of Deep Networks from Decentralized Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
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Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
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Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images
Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images
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BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
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Stride Length Estimation:
Stride Length Estimation:
Gaussian NLL Loss
Gaussian NLL Loss
Presenter: Min-Woo Tae (태민우)
Date: 11 May 2023
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MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
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Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings
Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings
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MLP-Mixer: An all-MLP Architecture for Vision
MLP-Mixer: An all-MLP Architecture for Vision
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Training Language Models to Follow Instructions with Human Feedback
Training Language Models to Follow Instructions with Human Feedback
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GraFormer: Graph Convolution Transformer for 3D Pose Estimation
GraFormer: Graph Convolution Transformer for 3D Pose Estimation
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Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
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ImageNet Classification with Deep Convolutional Neural Networks
ImageNet Classification with Deep Convolutional Neural Networks
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An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
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Vision GNN: An Image is Worth Graph of Nodes
Vision GNN: An Image is Worth Graph of Nodes
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DaViT: Dual Attention Vision Transformers
DaViT: Dual Attention Vision Transformers
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TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
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MedCLIP: Contrastive Learning from Unpaired Medical Images and Text
MedCLIP: Contrastive Learning from Unpaired Medical Images and Text
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Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
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Supervised Contrastive Learning
Supervised Contrastive Learning
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DART: Articulated Hand Model with Diverse Accessories and Rich Textures
DART: Articulated Hand Model with Diverse Accessories and Rich Textures
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Agent-Aware Dropout DQN for Safe and Efficient
Agent-Aware Dropout DQN for Safe and Efficient
On-line Dialogue Policy Learning
On-line Dialogue Policy Learning
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TabNet: Attentive Interpretable Tabular Learning
TabNet: Attentive Interpretable Tabular Learning