11 citations · 16 across the 7 of their papers we have counts for
7 papers
Seamless Interaction: Dyadic Audiovisual Motion Modeling and Large-Scale Dataset
Vasu Agrawal, Akinniyi Akinyemi, Kathryn Alvero +81
Human communication involves a complex interplay of verbal and nonverbal signals, essential for conveying meaning and achieving interpersonal goals. To develop socially intelligent…
Score-Guided Diffusion for 3D Human Recovery
Anastasis Stathopoulos, Ligong Han, Dimitris Metaxas
We present Score-Guided Human Mesh Recovery (ScoreHMR), an approach for solving inverse problems for 3D human pose and shape reconstruction. These inverse problems involve fitting…
Improving Tuning-Free Real Image Editing with Proximal Guidance
Ligong Han, Song Wen, Qi Chen +13
DDIM inversion has revealed the remarkable potential of real image editing within diffusion-based methods. However, the accuracy of DDIM reconstruction degrades as larger classifie…
Learning Articulated Shape with Keypoint Pseudo-labels from Web Images
Anastasis Stathopoulos, Georgios Pavlakos, Ligong Han +1
This paper shows that it is possible to learn models for monocular 3D reconstruction of articulated objects (e.g., horses, cows, sheep), using as few as 50-150 images labeled with…
Exploiting Unlabeled Data with Vision and Language Models for Object Detection
Shiyu Zhao, Zhixing Zhang, Samuel Schulter +5
Building robust and generic object detection frameworks requires scaling to larger label spaces and bigger training datasets. However, it is prohibitively costly to acquire annotat…
Dual Projection Generative Adversarial Networks for Conditional Image Generation
Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos +4
Conditional Generative Adversarial Networks (cGANs) extend the standard unconditional GAN framework to learning joint data-label distributions from samples, and have been establish…
Unbiased Auxiliary Classifier GANs with MINE
Ligong Han, Anastasis Stathopoulos, Tao Xue +1
Auxiliary Classifier GANs (AC-GANs) are widely used conditional generative models and are capable of generating high-quality images. Previous work has pointed out that AC-GAN learn…