6 citations · 8 across the 7 of their papers we have counts for
6 papers · 1 filter
Learning Semantic Latent Directions for Accurate and Controllable Human Motion Prediction
Guowei Xu, Jiale Tao, Wen Li +1
In the realm of stochastic human motion prediction (SHMP), researchers have often turned to generative models like GANS, VAEs and diffusion models. However, most previous approache…
Learning Motion Refinement for Unsupervised Face Animation
Jiale Tao, Shuhang Gu, Wen Li +1
Unsupervised face animation aims to generate a human face video based on the appearance of a source image, mimicking the motion from a driving video. Existing methods typically ado…
Motion and Appearance Adaptation for Cross-Domain Motion Transfer
Borun Xu, Biao Wang, Jinhong Deng +5
Motion transfer aims to transfer the motion of a driving video to a source image. When there are considerable differences between object in the driving video and that in the source…
Motion Transformer for Unsupervised Image Animation
Jiale Tao, Biao Wang, Tiezheng Ge +3
Image animation aims to animate a source image by using motion learned from a driving video. Current state-of-the-art methods typically use convolutional neural networks (CNNs) to…
Undoing the Damage of Label Shift for Cross-domain Semantic Segmentation
Yahao Liu, Jinhong Deng, Jiale Tao +3
Existing works typically treat cross-domain semantic segmentation (CDSS) as a data distribution mismatch problem and focus on aligning the marginal distribution or conditional dist…
Structure-Aware Motion Transfer with Deformable Anchor Model
Jiale Tao, Biao Wang, Borun Xu +4
Given a source image and a driving video depicting the same object type, the motion transfer task aims to generate a video by learning the motion from the driving video while prese…