105 citations · 148 across the 5 of their papers we have counts for
11 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…