activity
20172022
most citedAction Genome: Actions as Composition of Spatio-temporal Scene Graphs

17 citations · 36 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20222 cited

Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving

Mahyar Najibi, Jingwei Ji, Yin Zhou +4

Learning-based perception and prediction modules in modern autonomous driving systems typically rely on expensive human annotation and are designed to perceive only a handful of pr…

cs.CV2021

Home Action Genome: Cooperative Compositional Action Understanding

Nishant Rai, Haofeng Chen, Jingwei Ji +5

Existing research on action recognition treats activities as monolithic events occurring in videos. Recently, the benefits of formulating actions as a combination of atomic-actions…

cs.CV201917 cited

Action Genome: Actions as Composition of Spatio-temporal Scene Graphs

Jingwei Ji, Ranjay Krishna, Li Fei-Fei +1

Action recognition has typically treated actions and activities as monolithic events that occur in videos. However, there is evidence from Cognitive Science and Neuroscience that p…

cs.CV20191 cited

Learning Temporal Action Proposals With Fewer Labels

Jingwei Ji, Kaidi Cao, Juan Carlos Niebles

Temporal action proposals are a common module in action detection pipelines today. Most current methods for training action proposal modules rely on fully supervised approaches tha…

cs.CV201916 cited

Few-Shot Video Classification via Temporal Alignment

Kaidi Cao, Jingwei Ji, Zhangjie Cao +2

There is a growing interest in learning a model which could recognize novel classes with only a few labeled examples. In this paper, we propose Temporal Alignment Module (TAM), a n…

cs.CV2017

DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image

Andrey Kurenkov, Jingwei Ji, Animesh Garg +4

3D reconstruction from a single image is a key problem in multiple applications ranging from robotic manipulation to augmented reality. Prior methods have tackled this problem thro…