257 citations · 724 across the 15 of their papers we have counts for
15 papers
Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency
Qing Liu, Vignesh Ramanathan, Dhruv Mahajan +2
Weakly supervised instance segmentation reduces the cost of annotations required to train models. However, existing approaches which rely only on image-level class labels predomina…
SPAN: Spatial Pyramid Attention Network forImage Manipulation Localization
Xuefeng Hu, Zhihan Zhang, Zhenye Jiang +3
We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and localization of multiple types of image manipulations. The proposed architecture efficientl…
Activity Driven Weakly Supervised Object Detection
Zhenheng Yang, Dhruv Mahajan, Deepti Ghadiyaram +2
Weakly supervised object detection aims at reducing the amount of supervision required to train detection models. Such models are traditionally learned from images/videos labelled…
Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo Videos
Yang Wang, Zhenheng Yang, Peng Wang +3
Learning depth and optical flow via deep neural networks by watching videos has made significant progress recently. In this paper, we jointly solve the two tasks by exploiting the…
Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding
Chenxu Luo, Zhenheng Yang, Peng Wang +4
Learning to estimate 3D geometry in a single frame and optical flow from consecutive frames by watching unlabeled videos via deep convolutional network has made significant progres…
Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D Motion Understanding
Zhenheng Yang, Peng Wang, Yang Wang +2
Learning to estimate 3D geometry in a single image by watching unlabeled videos via deep convolutional network has made significant process recently. Current state-of-the-art (SOTA…
LEGO: Learning Edge with Geometry all at Once by Watching Videos
Zhenheng Yang, Peng Wang, Yang Wang +2
Learning to estimate 3D geometry in a single image by watching unlabeled videos via deep convolutional network is attracting significant attention. In this paper, we introduce a "3…
Unsupervised Learning of Geometry with Edge-aware Depth-Normal Consistency
Zhenheng Yang, Peng Wang, Wei Xu +2
Learning to reconstruct depths in a single image by watching unlabeled videos via deep convolutional network (DCN) is attracting significant attention in recent years. In this pape…
Occlusion Aware Unsupervised Learning of Optical Flow
Yang Wang, Yi Yang, Zhenheng Yang +3
It has been recently shown that a convolutional neural network can learn optical flow estimation with unsupervised learning. However, the performance of the unsupervised methods st…
Spatio-Temporal Action Detection with Cascade Proposal and Location Anticipation
Zhenheng Yang, Jiyang Gao, Ram Nevatia
In this work, we address the problem of spatio-temporal action detection in temporally untrimmed videos. It is an important and challenging task as finding accurate human actions i…
RED: Reinforced Encoder-Decoder Networks for Action Anticipation
Jiyang Gao, Zhenheng Yang, Ram Nevatia
Action anticipation aims to detect an action before it happens. Many real world applications in robotics and surveillance are related to this predictive capability. Current methods…
Cascaded Boundary Regression for Temporal Action Detection
Jiyang Gao, Zhenheng Yang, Ram Nevatia
Temporal action detection in long videos is an important problem. State-of-the-art methods address this problem by applying action classifiers on sliding windows. Although sliding…
TALL: Temporal Activity Localization via Language Query
Jiyang Gao, Chen Sun, Zhenheng Yang +1
This paper focuses on temporal localization of actions in untrimmed videos. Existing methods typically train classifiers for a pre-defined list of actions and apply them in a slidi…
TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals
Jiyang Gao, Zhenheng Yang, Chen Sun +2
Temporal Action Proposal (TAP) generation is an important problem, as fast and accurate extraction of semantically important (e.g. human actions) segments from untrimmed videos is…
A Multi-Scale Cascade Fully Convolutional Network Face Detector
Zhenheng Yang, Ram Nevatia
Face detection is challenging as faces in images could be present at arbitrary locations and in different scales. We propose a three-stage cascade structure based on fully convolut…