36 citations · 40 across the 5 of their papers we have counts for
8 papers
Inexact Proximal-Gradient Methods with Support Identification
Yutong Dai, Daniel P. Robinson
We consider the proximal-gradient method for minimizing an objective function that is the sum of a smooth function and a non-smooth convex function. A feature that distinguishes ou…
Boosting Robustness of Image Matting with Context Assembling and Strong Data Augmentation
Yutong Dai, Brian Price, He Zhang +1
Deep image matting methods have achieved increasingly better results on benchmarks (e.g., Composition-1k/alphamatting.com). However, the robustness, including robustness to trimaps…
Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data
Dezhong Yao, Wanning Pan, Yutong Dai +5
Federated learning enables multiple clients to collaboratively learn a global model by periodically aggregating the clients' models without transferring the local data. However, du…
Learning Affinity-Aware Upsampling for Deep Image Matting
Yutong Dai, Hao Lu, Chunhua Shen
We show that learning affinity in upsampling provides an effective and efficient approach to exploit pairwise interactions in deep networks. Second-order features are commonly used…
A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer
Frank E. Curtis, Yutong Dai, Daniel P. Robinson
We consider the problem of minimizing an objective function that is the sum of a convex function and a group sparsity-inducing regularizer. Problems that integrate such regularizer…
In defense of OSVOS
Yu Liu, Yutong Dai, Anh-Dzung Doan +2
As a milestone for video object segmentation, one-shot video object segmentation (OSVOS) has achieved a large margin compared to the conventional optical-flow based methods regardi…