69 citations · 70 across the 5 of their papers we have counts for
5 papers
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time
Chiao-An Yang, Ziwei Liu, Raymond A. Yeh
Subsampling layers play a crucial role in deep nets by discarding a portion of an activation map to reduce its spatial dimensions. This encourages the deep net to learn higher-leve…
Learning to Obstruct Few-Shot Image Classification over Restricted Classes
Amber Yijia Zheng, Chiao-An Yang, Raymond A. Yeh
Advancements in open-source pre-trained backbones make it relatively easy to fine-tune a model for new tasks. However, this lowered entry barrier poses potential risks, e.g., bad a…
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields
Joshua Ahn, Haochen Wang, Raymond A. Yeh +1
Scale-ambiguity in 3D scene dimensions leads to magnitude-ambiguity of volumetric densities in neural radiance fields, i.e., the densities double when scene size is halved, and vic…
Truly Scale-Equivariant Deep Nets with Fourier Layers
Md Ashiqur Rahman, Raymond A. Yeh
In computer vision, models must be able to adapt to changes in image resolution to effectively carry out tasks such as image segmentation; This is known as scale-equivariance. Rece…
Semantic Facial Expression Editing using Autoencoded Flow
Raymond Yeh, Ziwei Liu, Dan B Goldman +1
High-level manipulation of facial expressions in images --- such as changing a smile to a neutral expression --- is challenging because facial expression changes are highly non-lin…