132 citations · 164 across the 7 of their papers we have counts for
9 papers
FlexNeRF: Photorealistic Free-viewpoint Rendering of Moving Humans from Sparse Views
Vinoj Jayasundara, Amit Agrawal, Nicolas Heron +2
We present FlexNeRF, a method for photorealistic freeviewpoint rendering of humans in motion from monocular videos. Our approach works well with sparse views, which is a challengin…
Sequential Ensembling for Semantic Segmentation
Rawal Khirodkar, Brandon Smith, Siddhartha Chandra +2
Ensemble approaches for deep-learning-based semantic segmentation remain insufficiently explored despite the proliferation of competitive benchmarks and downstream applications. In…
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation
Rawal Khirodkar, Visesh Chari, Amit Agrawal +1
A key assumption of top-down human pose estimation approaches is their expectation of having a single person/instance present in the input bounding box. This often leads to failure…
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…