Search Results for author:
Found 9 papers, 2 papers with code
Deep Learning Recommendation Model for Personalization and Recommendation Systems
With the advent of deep learning, neural network-based recommendation models have emerged as an important tool for tackling personalization and recommendation tasks.
Time-based Sequence Model for Personalization and Recommendation Systems
In this paper we develop a novel recommendation model that explicitly incorporates time information.
Joint Multi-Person Pose Estimation and Semantic Part Segmentation
To refine part segments, the refined pose and the original part potential are integrated through a Part FCN, where the skeleton feature from pose serves as additional regularization cues for part segments.
Ranked #5 on
Human Part Segmentation
on PASCAL-Part
Ground-truth dataset and baseline evaluations for image base-detail separation algorithms
Base-detail separation is a fundamental computer vision problem consisting of modeling a smooth base layer with the coarse structures, and a detail layer containing the texture-like structures.
DeePM: A Deep Part-Based Model for Object Detection and Semantic Part Localization
In this paper, we propose a deep part-based model (DeePM) for symbiotic object detection and semantic part localization.
Parsing Occluded People by Flexible Compositions
We model humans using a graphical model which has a tree structure building on recent work [32, 6] and exploit the connectivity prior that, even in presence of occlusion, the visible nodes form a connected subtree of the graphical model.
Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations
More precisely, we specify a graphical model for human pose which exploits the fact the local image measurements can be used both to detect parts (or joints) and also to predict the spatial relationships between them (Image Dependent Pairwise Relations).
Ranked #18 on
Pose Estimation
on Leeds Sports Poses
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts
Our model automatically decouples the holistic object or body parts from the model when they are hard to detect.
The Role of Context for Object Detection and Semantic Segmentation in the Wild
In this paper we study the role of context in existing state-of-the-art detection and segmentation approaches.
