7 citations · 21 across the 10 of their papers we have counts for
10 papers
SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection
Yichen Xie, Chenfeng Xu, Marie-Julie Rakotosaona +5
By identifying four important components of existing LiDAR-camera 3D object detection methods (LiDAR and camera candidates, transformation, and fusion outputs), we observe that all…
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm
Yichen Xie, Han Lu, Junchi Yan +3
Given the large-scale data and the high annotation cost, pretraining-finetuning becomes a popular paradigm in multiple computer vision tasks. Previous research has covered both the…
AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains
Hao-Shu Fang, Chenxi Wang, Hongjie Fang +6
As the basis for prehensile manipulation, it is vital to enable robots to grasp as robustly as humans. Our innate grasping system is prompt, accurate, flexible, and continuous acro…
Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning
Zheng Wu, Yichen Xie, Wenzhao Lian +5
Humans are capable of abstracting various tasks as different combinations of multiple attributes. This perspective of compositionality is vital for human rapid learning and adaptio…
Towards General and Efficient Active Learning
Yichen Xie, Masayoshi Tomizuka, Wei Zhan
Active learning selects the most informative samples to exploit limited annotation budgets. Existing work follows a cumbersome pipeline that repeats the time-consuming model traini…
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds
Siyuan Huang, Yichen Xie, Song-Chun Zhu +1
To date, various 3D scene understanding tasks still lack practical and generalizable pre-trained models, primarily due to the intricate nature of 3D scene understanding tasks and t…
DecAug: Augmenting HOI Detection via Decomposition
Yichen Xie, Hao-Shu Fang, Dian Shao +2
Human-object interaction (HOI) detection requires a large amount of annotated data. Current algorithms suffer from insufficient training samples and category imbalance within datas…
Interpreting Multivariate Shapley Interactions in DNNs
Hao Zhang, Yichen Xie, Longjie Zheng +2
This paper aims to explain deep neural networks (DNNs) from the perspective of multivariate interactions. In this paper, we define and quantify the significance of interactions amo…
DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection
Hao-Shu Fang, Yichen Xie, Dian Shao +1
Recent years, human-object interaction (HOI) detection has achieved impressive advances. However, conventional two-stage methods are usually slow in inference. On the other hand, e…
Interpreting and Boosting Dropout from a Game-Theoretic View
Hao Zhang, Sen Li, Yinchao Ma +3
This paper aims to understand and improve the utility of the dropout operation from the perspective of game-theoretic interactions. We prove that dropout can suppress the strength…