29 citations · 91 across the 6 of their papers we have counts for
7 papers
Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks
Yen-Cheng Liu, Chih-Yao Ma, Junjiao Tian +2
Adapting large-scale pretrained models to various downstream tasks via fine-tuning is a standard method in machine learning. Recently, parameter-efficient fine-tuning methods show…
Unbiased Teacher for Semi-Supervised Object Detection
Yen-Cheng Liu, Chih-Yao Ma, Zijian He +6
Semi-supervised learning, i.e., training networks with both labeled and unlabeled data, has made significant progress recently. However, existing works have primarily focused on im…
One Shot 3D Photography
Johannes Kopf, Kevin Matzen, Suhib Alsisan +12
3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving…
FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining
Xiaoliang Dai, Alvin Wan, Peizhao Zhang +8
Neural Architecture Search (NAS) yields state-of-the-art neural networks that outperform their best manually-designed counterparts. However, previous NAS methods search for archite…
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions
Alvin Wan, Xiaoliang Dai, Peizhao Zhang +9
Differentiable Neural Architecture Search (DNAS) has demonstrated great success in designing state-of-the-art, efficient neural networks. However, DARTS-based DNAS's search space i…
Efficient Segmentation: Learning Downsampling Near Semantic Boundaries
Dmitrii Marin, Zijian He, Peter Vajda +4
Many automated processes such as auto-piloting rely on a good semantic segmentation as a critical component. To speed up performance, it is common to downsample the input frame. Ho…