most citedEfficient Continuous Pareto Exploration in Multi-Task Learning

30 citations · 36 across the 5 of their papers we have counts for

collaborators

10 papers

cs.LG202030 cited

Efficient Continuous Pareto Exploration in Multi-Task Learning

Pingchuan Ma, Tao Du, Wojciech Matusik

Tasks in multi-task learning often correlate, conflict, or even compete with each other. As a result, a single solution that is optimal for all tasks rarely exists. Recent papers i…

cs.CV2020

A Content Transformation Block For Image Style Transfer

Dmytro Kotovenko, Artsiom Sanakoyeu, Pingchuan Ma +2

Style transfer has recently received a lot of attention, since it allows to study fundamental challenges in image understanding and synthesis. Recent work has significantly improve…

eess.AS2020

Visually Guided Self Supervised Learning of Speech Representations

Abhinav Shukla, Konstantinos Vougioukas, Pingchuan Ma +2

Self supervised representation learning has recently attracted a lot of research interest for both the audio and visual modalities. However, most works typically focus on a particu…

cs.CV2020

Lipreading using Temporal Convolutional Networks

Brais Martinez, Pingchuan Ma, Stavros Petridis +1

Lip-reading has attracted a lot of research attention lately thanks to advances in deep learning. The current state-of-the-art model for recognition of isolated words in-the-wild c…

cs.CV20194 cited

Learning Efficient Video Representation with Video Shuffle Networks

Pingchuan Ma, Yao Zhou, Yu Lu +1

3D CNN shows its strong ability in learning spatiotemporal representation in recent video recognition tasks. However, inflating 2D convolution to 3D inevitably introduces additiona…

cs.CV20191 cited

Towards Pose-invariant Lip-Reading

Shiyang Cheng, Pingchuan Ma, Georgios Tzimiropoulos +4

Lip-reading models have been significantly improved recently thanks to powerful deep learning architectures. However, most works focused on frontal or near frontal views of the mou…