Search Results for author:
Found 23 papers, 8 papers with code
Transformer-Based Learned Optimization
We propose a new approach to learned optimization where we represent the computation of an optimizer's update step using a neural network.
Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Video
We focus on the task of estimating a physically plausible articulated human motion from monocular video.
Ranked #296 on
3D Human Pose Estimation
on Human3.6M
Differentiable Dynamics for Articulated 3d Human Motion Reconstruction
We introduce DiffPhy, a differentiable physics-based model for articulated 3d human motion reconstruction from video.
Ranked #46 on
3D Human Pose Estimation
on Human3.6M
Efficient Full Image Interactive Segmentation by Leveraging Within-image Appearance Similarity
We leverage a key observation: propagation from labeled to unlabeled pixels does not necessarily require class-specific knowledge, but can be done purely based on appearance similarity within an image.
Panoptic Image Annotation with a Collaborative Assistant
This paper aims to reduce the time to annotate images for panoptic segmentation, which requires annotating segmentation masks and class labels for all object instances and stuff regions.
Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation
As opposed to performing a series of small annotation tasks in isolation, we propose a unified interface for full image annotation in a single pass.
PoseTrack: A Benchmark for Human Pose Estimation and Tracking
In this work, we aim to further advance the state of the art by establishing "PoseTrack", a new large-scale benchmark for video-based human pose estimation and articulated tracking, and bringing together the community of researchers working on visual human analysis.
Ranked #3 on
Multi-Person Pose Estimation
on PoseTrack2017
Multiple People Tracking by Lifted Multicut and Person Re-Identification
This allows us to reward tracks that assign detections of similar appearance to the same person in a way that does not introduce implausible solutions.
ArtTrack: Articulated Multi-person Tracking in the Wild
In this paper we propose an approach for articulated tracking of multiple people in unconstrained videos.
Ranked #7 on
Keypoint Detection
on MPII Multi-Person
3D Pictorial Structures Revisited: Multiple Human Pose Estimation
We address the problem of 3D pose estimation of multiple humans from multiple views.
Ranked #15 on
3D Multi-Person Pose Estimation
on Campus
Multi-Person Tracking by Multicut and Deep Matching
In [1], we proposed a graph-based formulation that links and clusters person hypotheses over time by solving a minimum cost subgraph multicut problem.
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
The goal of this paper is to advance the state-of-the-art of articulated pose estimation in scenes with multiple people.
Ranked #1 on
Multi-Person Pose Estimation
on WAF
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
This paper considers the task of articulated human pose estimation of multiple people in real world images.
Ranked #2 on
Multi-Person Pose Estimation
on WAF
Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos
Every moment counts in action recognition.
Ranked #7 on
Action Detection
on Multi-THUMOS
End-to-end people detection in crowded scenes
Current people detectors operate either by scanning an image in a sliding window fashion or by classifying a discrete set of proposals.
An Empirical Evaluation of Deep Learning on Highway Driving
We collect a large data set of highway data and apply deep learning and computer vision algorithms to problems such as car and lane detection.
Ranked #2 on
Lane Detection
on Caltech Lanes Cordova
Recognizing Fine-Grained and Composite Activities using Hand-Centric Features and Script Data
To attack the second challenge, recognizing composite activities, we leverage the fact that these activities are compositional and that the essential components of the activities can be obtained from textual descriptions or scripts.
Fine-grained Activity Recognition with Holistic and Pose based Features
Holistic methods based on dense trajectories are currently the de facto standard for recognition of human activities in video.
3D Pictorial Structures for Multiple Human Pose Estimation
In this work, we address the problem of 3D pose estimation of multiple humans from multiple views.
Ranked #24 on
3D Multi-Person Pose Estimation
on Shelf
2D Human Pose Estimation: New Benchmark and State of the Art Analysis
Human pose estimation has made significant progress during the last years.
Coherent Multi-Sentence Video Description with Variable Level of Detail
Humans can easily describe what they see in a coherent way and at varying level of detail.
Learning Human Pose Estimation Features with Convolutional Networks
This paper introduces a new architecture for human pose estimation using a multi- layer convolutional network architecture and a modified learning technique that learns low-level features and higher-level weak spatial models.
Poselet Conditioned Pictorial Structures
In this paper we consider the challenging problem of articulated human pose estimation in still images.
