61 citations · 93 across the 10 of their papers we have counts for
11 papers
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles
Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya +10
Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance. While these components lead to effect…
Occupancy Planes for Single-view RGB-D Human Reconstruction
Xiaoming Zhao, Yuan-Ting Hu, Zhongzheng Ren +1
Single-view RGB-D human reconstruction with implicit functions is often formulated as per-point classification. Specifically, a set of 3D locations within the view-frustum of the c…
Total Variation Optimization Layers for Computer Vision
Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren +1
Optimization within a layer of a deep-net has emerged as a new direction for deep-net layer design. However, there are two main challenges when applying these layers to computer vi…
Equivariance Discovery by Learned Parameter-Sharing
Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson +1
Designing equivariance as an inductive bias into deep-nets has been a prominent approach to build effective models, e.g., a convolutional neural network incorporates translation eq…
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data
Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh +1
Extracting detailed 3D information of objects from video data is an important goal for holistic scene understanding. While recent methods have shown impressive results when reconst…
Chirality Nets for Human Pose Regression
Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing
We propose Chirality Nets, a family of deep nets that is equivariant to the "chirality transform," i.e., the transformation to create a chiral pair. Through parameter sharing, odd…
Max-Sliced Wasserstein Distance and its use for GANs
Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun +6
Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image…
Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation
Yuan-Ting Hu, Jia-Bin Huang, Alexander G. Schwing
Unsupervised video segmentation plays an important role in a wide variety of applications from object identification to compression. However, to date, fast motion, motion blur and…
VideoMatch: Matching based Video Object Segmentation
Yuan-Ting Hu, Jia-Bin Huang, Alexander G. Schwing
Video object segmentation is challenging yet important in a wide variety of applications for video analysis. Recent works formulate video object segmentation as a prediction task u…
MaskRNN: Instance Level Video Object Segmentation
Yuan-Ting Hu, Jia-Bin Huang, Alexander G. Schwing
Instance level video object segmentation is an important technique for video editing and compression. To capture the temporal coherence, in this paper, we develop MaskRNN, a recurr…
Descriptor Ensemble: An Unsupervised Approach to Descriptor Fusion in the Homography Space
Yuan-Ting Hu, Yen-Yu Lin, Hsin-Yi Chen +2
With the aim to improve the performance of feature matching, we present an unsupervised approach to fuse various local descriptors in the space of homographies. Inspired by the obs…