19 citations · 25 across the 2 of their papers we have counts for
6 papers
PoseNet3D: Learning Temporally Consistent 3D Human Pose via Knowledge Distillation
Shashank Tripathi, Siddhant Ranade, Ambrish Tyagi +1
Recovering 3D human pose from 2D joints is a highly unconstrained problem. We propose a novel neural network framework, PoseNet3D, that takes 2D joints as input and outputs 3D skel…
Unsupervised 3D Pose Estimation with Geometric Self-Supervision
Ching-Hang Chen, Ambrish Tyagi, Amit Agrawal +4
We present an unsupervised learning approach to recover 3D human pose from 2D skeletal joints extracted from a single image. Our method does not require any multi-view image data,…
Learning to Generate Synthetic Data via Compositing
Shashank Tripathi, Siddhartha Chandra, Amit Agrawal +3
We present a task-aware approach to synthetic data generation. Our framework employs a trainable synthesizer network that is optimized to produce meaningful training samples by ass…
Can 3D Pose be Learned from 2D Projections Alone?
Dylan Drover, Rohith MV, Ching-Hang Chen +3
3D pose estimation from a single image is a challenging task in computer vision. We present a weakly supervised approach to estimate 3D pose points, given only 2D pose landmarks. O…
CRAFT: Complementary Recommendations Using Adversarial Feature Transformer
Cong Phuoc Huynh, Arridhana Ciptadi, Ambrish Tyagi +1
Traditional approaches for complementary product recommendations rely on behavioral and non-visual data such as customer co-views or co-buys. However, certain domains such as fashi…
Context Encoding for Semantic Segmentation
Hang Zhang, Kristin Dana, Jianping Shi +4
Recent work has made significant progress in improving spatial resolution for pixelwise labeling with Fully Convolutional Network (FCN) framework by employing Dilated/Atrous convol…