411 citations · 467 across the 14 of their papers we have counts for
6 papers · 1 filter
Infusing Definiteness into Randomness: Rethinking Composition Styles for Deep Image Matting
Zixuan Ye, Yutong Dai, Chaoyi Hong +2
We study the composition style in deep image matting, a notion that characterizes a data generation flow on how to exploit limited foregrounds and random backgrounds to form a trai…
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…
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…
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…
Indices Matter: Learning to Index for Deep Image Matting
Hao Lu, Yutong Dai, Chunhua Shen +1
We show that existing upsampling operators can be unified with the notion of the index function. This notion is inspired by an observation in the decoding process of deep image mat…
Index Network
Hao Lu, Yutong Dai, Chunhua Shen +1
We show that existing upsampling operators can be unified using the notion of the index function. This notion is inspired by an observation in the decoding process of deep image ma…