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Found 14 papers, 5 papers with code
Using Augmented Face Images to Improve Facial Recognition Tasks
We present a framework that uses GAN-augmented images to complement certain specific attributes, usually underrepresented, for machine learning model training.
High-Quality Pluralistic Image Completion via Code Shared VQGAN
In this work, we present a novel framework for pluralistic image completion that can achieve both high quality and diversity at much faster inference speed.
DynOcc: Learning Single-View Depth from Dynamic Occlusion Cues
Recently, significant progress has been made in single-view depth estimation thanks to increasingly large and diverse depth datasets.
HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures
We present HoliCity, a city-scale 3D dataset with rich structural information.
Dynamic Kernel Distillation for Efficient Pose Estimation in Videos
Existing video-based human pose estimation methods extensively apply large networks onto every frame in the video to localize body joints, which suffer high computational cost and hardly meet the low-latency requirement in realistic applications.
Task-Assisted Domain Adaptation with Anchor Tasks
Our key idea to improve domain adaptation is to introduce a separate anchor task (such as facial landmarks) whose annotations can be obtained at no cost or are already available on both synthetic and real datasets.
Transformable Bottleneck Networks
We propose a novel approach to performing fine-grained 3D manipulation of image content via a convolutional neural network, which we call the Transformable Bottleneck Network (TBN).
Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion
In particular, instead of only performing scene completion from each individual scan, our approach alternates between relative pose estimation and scene completion.
Deep Volumetric Video From Very Sparse Multi-View Performance Capture
We present a deep learning-based volumetric capture approach for performance capture using a passive and highly sparse multi-view capture system.
Deep Generative Modeling for Scene Synthesis via Hybrid Representations
We show a principled way to train this model by combining discriminator losses for both a 3D object arrangement representation and a 2D image-based representation.
StarMap for Category-Agnostic Keypoint and Viewpoint Estimation
Existing methods define semantic keypoints separately for each category with a fixed number of semantic labels in fixed indices.
Ranked #2 on
Keypoint Detection
on Pascal3D+
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency
In this paper, we introduce a novel unsupervised domain adaptation technique for the task of 3D keypoint prediction from a single depth scan or image.
AutoScaler: Scale-Attention Networks for Visual Correspondence
We propose AutoScaler, a scale-attention network to explicitly optimize this trade-off in visual correspondence tasks.
Wide-Baseline Hair Capture Using Strand-Based Refinement
We propose a novel algorithm to reconstruct the 3D geometry of human hairs in wide-baseline setups using strand-based refinement.
