412 citations · 1.9k across the 48 of their papers we have counts for
50 papers
Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations
Atsuhiro Noguchi, Xiao Sun, Stephen Lin +1
We propose an unsupervised method for 3D geometry-aware representation learning of articulated objects, in which no image-pose pairs or foreground masks are used for training. Thou…
Towards Tokenized Human Dynamics Representation
Kenneth Li, Xiao Sun, Zhirong Wu +2
For human action understanding, a popular research direction is to analyze short video clips with unambiguous semantic content, such as jumping and drinking. However, methods for u…
The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
Runtao Liu, Zhirong Wu, Stella X. Yu +1
Humans can easily segment moving objects without knowing what they are. That objectness could emerge from continuous visual observations motivates us to model grouping and movement…
Bootstrap Your Object Detector via Mixed Training
Mengde Xu, Zheng Zhang, Fangyun Wei +5
We introduce MixTraining, a new training paradigm for object detection that can improve the performance of existing detectors for free. MixTraining enhances data augmentation by ut…
ACP++: Action Co-occurrence Priors for Human-Object Interaction Detection
Dong-Jin Kim, Xiao Sun, Jinsoo Choi +2
A common problem in the task of human-object interaction (HOI) detection is that numerous HOI classes have only a small number of labeled examples, resulting in training sets with…
Video Swin Transformer
Ze Liu, Jia Ning, Yue Cao +4
The vision community is witnessing a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major video recognition benchm…