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Found 17 papers, 5 papers with code
Harry Potter's Marauder's Map: Localizing and Tracking Multiple Persons-of-Interest by Nonnegative Discretization
A device just like Harry Potter's Marauder's Map, which pinpoints the location of each person-of-interest at all times, provides invaluable information for analysis of surveillance videos.
Self-Paced Learning with Diversity
Self-paced learning (SPL) is a recently proposed learning regime inspired by the learning process of humans and animals that gradually incorporates easy to more complex samples into training.
The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition
First, we propose a two-stream Stacked Convolutional Independent Subspace Analysis (ConvISA) architecture to show that unsupervised learning methods can significantly boost the performance of traditional local features extracted from data-independent models.
Handcrafted Local Features are Convolutional Neural Networks
We approach this problem by first showing that local handcrafted features and Convolutional Neural Networks (CNNs) share the same convolution-pooling network structure.
Improving Human Activity Recognition Through Ranking and Re-ranking
We propose two well-motivated ranking-based methods to enhance the performance of current state-of-the-art human activity recognition systems.
Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization
Therefore, our tracker propagates identity information to frames without recognized faces by uncovering the appearance and spatial manifold formed by person detections.
The Solution Path Algorithm for Identity-Aware Multi-Object Tracking
The tracker is formulated as a quadratic optimization problem with L0 norm constraints, which we propose to solve with the solution path algorithm.
Strategies for Searching Video Content with Text Queries or Video Examples
The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search.
Learning Patch Reconstructability for Accelerating Multi-View Stereo
By prioritizing stereo matching on a subset of patches that are highly reconstructable and also cover the 3D surface, we are able to accelerate MVS with minimal reduction in accuracy and completeness.
Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors
In this paper, we present supervision-by-registration, an unsupervised approach to improve the precision of facial landmark detectors on both images and video.
Ranked #1 on
Facial Landmark Detection
on 300-VW (C)
Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
In this paper, we propose a self-supervised domain adaptation approach to enable the animation of high-fidelity face models from a commodity camera.
Epipolar Transformers
The intuition is: given a 2D location p in the current view, we would like to first find its corresponding point p' in a neighboring view, and then combine the features at p' with the features at p, thus leading to a 3D-aware feature at p. Inspired by stereo matching, the epipolar transformer leverages epipolar constraints and feature matching to approximate the features at p'.
Ranked #1 on
3D Hand Pose Estimation
on InterHand2.6M
InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image
Therefore, we firstly propose (1) a large-scale dataset, InterHand2. 6M, and (2) a baseline network, InterNet, for 3D interacting hand pose estimation from a single RGB image.
Ranked #8 on
3D Interacting Hand Pose Estimation
on InterHand2.6M
Supervision by Registration and Triangulation for Landmark Detection
End-to-end training is made possible by differentiable registration and 3D triangulation modules.
CodedStereo: Learned Phase Masks for Large Depth-of-field Stereo
Conventional stereo suffers from a fundamental trade-off between imaging volume and signal-to-noise ratio (SNR) -- due to the conflicting impact of aperture size on both these variables.
Multiface: A Dataset for Neural Face Rendering
Along with the release of the dataset, we conduct ablation studies on the influence of different model architectures toward the model's interpolation capacity of novel viewpoint and expressions.
URHand: Universal Relightable Hands
To simplify the personalization process while retaining photorealism, we build a powerful universal relightable prior based on neural relighting from multi-view images of hands captured in a light stage with hundreds of identities.
