activity
20172021
most citedDUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces

11 citations · 26 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV20214 cited

3D Human Pose, Shape and Texture from Low-Resolution Images and Videos

Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer +2

3D human pose and shape estimation from monocular images has been an active research area in computer vision. Existing deep learning methods for this task rely on high-resolution i…

cs.CV202011 cited

DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces

Rahul Venkatesh, Sarthak Sharma, Aurobrata Ghosh +2

High fidelity representation of shapes with arbitrary topology is an important problem for a variety of vision and graphics applications. Owing to their limited resolution, classic…

cs.CV2020

Synthetic Expressions are Better Than Real for Learning to Detect Facial Actions

Koichiro Niinuma, Itir Onal Ertugrul, Jeffrey F Cohn +1

Critical obstacles in training classifiers to detect facial actions are the limited sizes of annotated video databases and the relatively low frequencies of occurrence of many acti…

cs.CV20204 cited

3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning

Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer +2

3D human shape and pose estimation from monocular images has been an active area of research in computer vision, having a substantial impact on the development of new applications,…

cs.CV2018

Brute-Force Facial Landmark Analysis With A 140,000-Way Classifier

Mengtian Li, Laszlo Jeni, Deva Ramanan

We propose a simple approach to visual alignment, focusing on the illustrative task of facial landmark estimation. While most prior work treats this as a regression problem, we ins…

cs.CV20177 cited

FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge

Michel F. Valstar, Enrique Sánchez-Lozano, Jeffrey F. Cohn +5

The field of Automatic Facial Expression Analysis has grown rapidly in recent years. However, despite progress in new approaches as well as benchmarking efforts, most evaluations s…