activity
20132022
most citedSparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach

179 citations · 227 across the 16 of their papers we have counts for

collaborators

36 papers

cs.CV20227 cited

Contact-aware Human Motion Forecasting

Wei Mao, Miaomiao Liu, Richard Hartley +1

In this paper, we tackle the task of scene-aware 3D human motion forecasting, which consists of predicting future human poses given a 3D scene and a past human motion. A key challe…

cs.CV2021

Invertible Attention

Jiajun Zha, Yiran Zhong, Jing Zhang +2

Attention has been proved to be an efficient mechanism to capture long-range dependencies. However, so far it has not been deployed in invertible networks. This is due to the fact…

cs.CV20212 cited

One Ring to Rule Them All: a simple solution to multi-view 3D-Reconstruction of shapes with unknown BRDF via a small Recurrent ResNet

Ziang Cheng, Hongdong Li, Richard Hartley +2

This paper proposes a simple method which solves an open problem of multi-view 3D-Reconstruction for objects with unknown and generic surface materials, imaged by a freely moving c…

cs.CV20211 cited

Learning Optical Flow from a Few Matches

Shihao Jiang, Yao Lu, Hongdong Li +1

State-of-the-art neural network models for optical flow estimation require a dense correlation volume at high resolutions for representing per-pixel displacement. Although the dens…

cs.CV2021

Learning to Estimate Hidden Motions with Global Motion Aggregation

Shihao Jiang, Dylan Campbell, Yao Lu +2

Occlusions pose a significant challenge to optical flow algorithms that rely on local evidences. We consider an occluded point to be one that is imaged in the first frame but not i…

cs.CV2021

Few-shot Weakly-Supervised Object Detection via Directional Statistics

Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan +2

Detecting novel objects from few examples has become an emerging topic in computer vision recently. However, these methods need fully annotated training images to learn new object…