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09/06/2023
Distribution-Aware Prompt Tuning for Vision-Language Models
Pre-trained vision-language models (VLMs) have shown impressive performa...
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08/29/2023
Read-only Prompt Optimization for Vision-Language Few-shot Learning
In recent years, prompt tuning has proven effective in adapting pre-trai...
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08/23/2023
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification
Interpretability is a crucial factor in building reliable models for var...
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08/23/2023
Semantic-Aware Implicit Template Learning via Part Deformation Consistency
Learning implicit templates as neural fields has recently shown impressi...
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08/18/2023
Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models
Video Question Answering (VideoQA) is a challenging task that entails co...
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03/29/2023
Self-positioning Point-based Transformer for Point Cloud Understanding
Transformers have shown superior performance on various computer vision ...
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03/23/2023
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models
Foundation models have shown outstanding performance and generalization ...
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03/20/2023
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignment
The application of modern machine learning to retinal image analyses off...
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03/05/2023
Semantic-aware Occlusion Filtering Neural Radiance Fields in the Wild
We present a learning framework for reconstructing neural scene represen...
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02/03/2023
Robust Camera Pose Refinement for Multi-Resolution Hash Encoding
Multi-resolution hash encoding has recently been proposed to reduce the ...
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02/02/2023
Domain Generalization Emerges from Dreaming
Recent studies have proven that DNNs, unlike human vision, tend to explo...
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12/02/2022
Relation-aware Language-Graph Transformer for Question Answering
Question Answering (QA) is a task that entails reasoning over natural la...
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10/15/2022
Invertible Monotone Operators for Normalizing Flows
Normalizing flows model probability distributions by learning invertible...
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10/14/2022
TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers
Mixup is a commonly adopted data augmentation technique for image classi...
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10/13/2022
SageMix: Saliency-Guided Mixup for Point Clouds
Data augmentation is key to improving the generalization ability of deep...
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06/29/2022
Deformable Graph Transformer
Transformer-based models have been widely used and achieved state-of-the...
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06/09/2022
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction
Graph Neural Networks (GNNs) have been widely applied to various fields ...
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04/11/2022
Consistency Learning via Decoding Path Augmentation for Transformers in Human Object Interaction Detection
Human-Object Interaction detection is a holistic visual recognition task...
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03/31/2022
Video-Text Representation Learning via Differentiable Weak Temporal Alignment
Learning generic joint representations for video and text by a supervise...
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03/26/2022
Metropolis-Hastings Data Augmentation for Graph Neural Networks
Graph Neural Networks (GNNs) often suffer from weak-generalization due t...
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01/05/2022
Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones
We aim to detect and identify multiple objects using multiple cameras an...
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12/29/2021
Deformable Graph Convolutional Networks
Graph neural networks (GNNs) have significantly improved the representat...
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10/11/2021
Point Cloud Augmentation with Weighted Local Transformations
Despite the extensive usage of point clouds in 3D vision, relatively lim...
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06/11/2021
Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs
Graph Neural Networks (GNNs) have been widely applied to various fields ...
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04/28/2021
HOTR: End-to-End Human-Object Interaction Detection with Transformers
Human-Object Interaction (HOI) detection is a task of identifying "a set...
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03/01/2021
Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
In recent years, graph neural networks (GNNs) have been widely adopted i...
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10/20/2020
Robust Neural Networks inspired by Strong Stability Preserving Runge-Kutta methods
Deep neural networks have achieved state-of-the-art performance in a var...
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07/16/2020
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
Graph neural networks have shown superior performance in a wide range of...
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11/29/2019
Unpaired Image Translation via Adaptive Convolution-based Normalization
Disentangling content and style information of an image has played an im...
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04/07/2019
ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classification
Deep convolutional neural networks have achieved remarkable success in c...
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11/20/2017
