7 citations · 19 across the 11 of their papers we have counts for
11 papers
OV-DEIM: Real-time DETR-Style Open-Vocabulary Object Detection with GridSynthetic Augmentation
Leilei Wang, Longfei Liu, Xi Shen +4
Real-time open-vocabulary object detection (OVOD) is essential for practical deployment in dynamic environments, where models must recognize a large and evolving set of categories…
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
Qinghua Tao, Francesco Tonin, Alex Lambert +3
In contrast with Mercer kernel-based approaches as used e.g., in Kernel Principal Component Analysis (KPCA), it was previously shown that Singular Value Decomposition (SVD) inheren…
SURE: SUrvey REcipes for building reliable and robust deep networks
Yuting Li, Yingyi Chen, Xuanlong Yu +2
In this paper, we revisit techniques for uncertainty estimation within deep neural networks and consolidate a suite of techniques to enhance their reliability. Our investigation re…
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen, Qinghua Tao, Francesco Tonin +1
While the great capability of Transformers significantly boosts prediction accuracy, it could also yield overconfident predictions and require calibrated uncertainty estimation, wh…
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
Yingyi Chen, Qinghua Tao, Francesco Tonin +1
Recently, a new line of works has emerged to understand and improve self-attention in Transformers by treating it as a kernel machine. However, existing works apply the methods for…
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer
Yingyi Chen, Xi Shen, Yahui Liu +2
The success of Vision Transformer (ViT) in various computer vision tasks has promoted the ever-increasing prevalence of this convolution-free network. The fact that ViT works on im…