• Publications
  • Influence
Learning Spatiotemporal Features with 3D Convolutional Networks
We propose a simple, yet effective approach for spatiotemporal feature learning using deep 3-dimensional convolutional networks (3D ConvNets) trained on a large scale supervised video dataset. OurExpand
  • 3,404
  • 795
  • Open Access
Interactive Facial Feature Localization
We address the problem of interactive facial feature localization from a single image. Our goal is to obtain an accurate segmentation of facial features on high-resolution images under a variety ofExpand
  • 647
  • 177
  • Open Access
Poselets: Body part detectors trained using 3D human pose annotations
We address the classic problems of detection, segmentation and pose estimation of people in images with a novel definition of a part, a poselet. We postulate two criteria (1) It should be easy toExpand
  • 991
  • 105
  • Open Access
Semantic contours from inverse detectors
We study the challenging problem of localizing and classifying category-specific object contours in real world images. For this purpose, we present a simple yet effective method for combining genericExpand
  • 740
  • 80
  • Open Access
PANDA: Pose Aligned Networks for Deep Attribute Modeling
We propose a method for inferring human attributes (such as gender, hair style, clothes style, expression, action) from images of people under large variation of viewpoint, pose, appearance,Expand
  • 419
  • 57
  • Open Access
C3D: Generic Features for Video Analysis
Videos have become ubiquitous due to the ease of capturing and sharing via social platforms like Youtube, Facebook, Instagram, and others. The computer vision community has tried to tackle variousExpand
  • 278
  • 53
  • Open Access
Robust object detection via soft cascade
We describe a method for training object detectors using a generalization of the cascade architecture, which results in a detection rate and speed comparable to that of the best published detectorsExpand
  • 366
  • 48
  • Open Access
Real-Time Adaptive Image Compression
We present a machine learning-based approach to lossy image compression which outperforms all existing codecs, while running in real-time. Our algorithm typically produces files 2.5 times smallerExpand
  • 248
  • 40
  • Open Access
Detecting People Using Mutually Consistent Poselet Activations
Bourdev and Malik (ICCV 09) introduced a new notion of parts, poselets, constructed to be tightly clustered both in the configuration space of keypoints, as well as in the appearance space of imageExpand
  • 392
  • 36
  • Open Access
Describing people: A poselet-based approach to attribute classification
We propose a method for recognizing attributes, such as the gender, hair style and types of clothes of people under large variation in viewpoint, pose, articulation and occlusion typical of personalExpand
  • 330
  • 34
  • Open Access