311 citations · 979 across the 36 of their papers we have counts for
7 papers · 1 filter
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics
Xinchen Yan, Akash Rastogi, Ruben Villegas +5
Long-term human motion can be represented as a series of motion modes---motion sequences that capture short-term temporal dynamics---with transitions between them. We leverage this…
Learning Blind Video Temporal Consistency
Wei-Sheng Lai, Jia-Bin Huang, Oliver Wang +3
Applying image processing algorithms independently to each frame of a video often leads to undesired inconsistent results over time. Developing temporally consistent video-based ex…
iMapper: Interaction-guided Joint Scene and Human Motion Mapping from Monocular Videos
Aron Monszpart, Paul Guerrero, Duygu Ceylan +2
A long-standing challenge in scene analysis is the recovery of scene arrangements under moderate to heavy occlusion, directly from monocular video. While the problem remains a subj…
Self-supervised Multi-view Person Association and Its Applications
Minh Vo, Ersin Yumer, Kalyan Sunkavalli +3
Reliable markerless motion tracking of people participating in a complex group activity from multiple moving cameras is challenging due to frequent occlusions, strong viewpoint and…
PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image
Chen Liu, Jimei Yang, Duygu Ceylan +2
This paper proposes a deep neural network (DNN) for piece-wise planar depthmap reconstruction from a single RGB image. While DNNs have brought remarkable progress to single-image d…
BodyNet: Volumetric Inference of 3D Human Body Shapes
Gül Varol, Duygu Ceylan, Bryan Russell +4
Human shape estimation is an important task for video editing, animation and fashion industry. Predicting 3D human body shape from natural images, however, is highly challenging du…
ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing
Chen-Hsuan Lin, Ersin Yumer, Oliver Wang +2
We address the problem of finding realistic geometric corrections to a foreground object such that it appears natural when composited into a background image. To achieve this, we p…