no code implementations • 29 Jul 2024 • Mingyu Zhang, Jiting Cai, MingYu Liu, Yue Xu, Cewu Lu, Yong-Lu Li
Given our findings, we establish design principles for visual reasoning frameworks following the separated symbolization and shared reasoning.
1 code implementation • 20 Jul 2024 • Xinyu Xu, Shengcheng Luo, Yanchao Yang, Yong-Lu Li, Cewu Lu
Building a general-purpose intelligent home-assistant agent skilled in diverse tasks by human commands is a long-term blueprint of embodied AI research, which poses requirements on task planning, environment modeling, and object interaction.
no code implementations • 29 Jun 2024 • Shengcheng Luo, Quanquan Peng, Jun Lv, Kaiwen Hong, Katherine Rose Driggs-Campbell, Cewu Lu, Yong-Lu Li
In this study, we introduce a novel system for joint learning between human operators and robots, that enables human operators to share control of a robot end-effector with a learned assistive agent, facilitating simultaneous human demonstration collection and robot manipulation teaching.
1 code implementation • 6 Jun 2024 • Yue Xu, Zhilin Lin, Yusong Qiu, Cewu Lu, Yong-Lu Li
Though dataset distillation has witnessed rapid development in recent years, the distillation of multimodal data, e. g., image-text pairs, poses unique and under-explored challenges.
no code implementations • 17 Dec 2023 • SiQi Liu, Yong-Lu Li, Zhou Fang, Xinpeng Liu, Yang You, Cewu Lu
To explore an effective embedding of HAOI for the machine, we build a new benchmark on 3D HAOI consisting of primitives together with their images and propose a task requiring machines to recover 3D HAOI using primitives from images.
no code implementations • 5 Dec 2023 • Xinpeng Liu, Haowen Hou, Yanchao Yang, Yong-Lu Li, Cewu Lu
High-quality data with simultaneously captured human and 3D environments is hard to acquire, resulting in limited data diversity and complexity.
1 code implementation • CVPR 2024 • Ziyu Wang, Yue Xu, Cewu Lu, Yong-Lu Li
It first distills the videos into still images as static memory and then compensates the dynamic and motion information with a learnable dynamic memory block.
no code implementations • NeurIPS 2023 • Xiaoqian Wu, Yong-Lu Li, Jianhua Sun, Cewu Lu
One possible path of activity reasoning is building a symbolic system composed of symbols and rules, where one rule connects multiple symbols, implying human knowledge and reasoning abilities.
no code implementations • 6 Oct 2023 • Xinpeng Liu, Yong-Lu Li, Ailing Zeng, Zizheng Zhou, Yang You, Cewu Lu
Motion understanding aims to establish a reliable mapping between motion and action semantics, while it is a challenging many-to-many problem.
no code implementations • ICCV 2023 • Yue Xu, Yong-Lu Li, Zhemin Huang, Michael Xu Liu, Cewu Lu, Yu-Wing Tai, Chi-Keung Tang
With the surge in attention to Egocentric Hand-Object Interaction (Ego-HOI), large-scale datasets such as Ego4D and EPIC-KITCHENS have been proposed.
2 code implementations • 28 May 2023 • Yue Xu, Yong-Lu Li, Kaitong Cui, Ziyu Wang, Cewu Lu, Yu-Wing Tai, Chi-Keung Tang
We believe this paradigm will open up new avenues in the dynamics of distillation and pave the way for efficient dataset distillation.
no code implementations • CVPR 2024 • Yong-Lu Li, Xiaoqian Wu, Xinpeng Liu, Zehao Wang, Yiming Dou, Yikun Ji, Junyi Zhang, Yixing Li, Jingru Tan, Xudong Lu, Cewu Lu
By aligning the classes of previous datasets to our semantic space, we gather (image/video/skeleton/MoCap) datasets into a unified database in a unified label system, i. e., bridging "isolated islands" into a "Pangea".
no code implementations • ICCV 2023 • Yong-Lu Li, Yue Xu, Xinyu Xu, Xiaohan Mao, Yuan YAO, SiQi Liu, Cewu Lu
To support OCL, we build a densely annotated knowledge base including extensive labels for three levels of object concept (category, attribute, affordance), and the causal relations of three levels.
1 code implementation • 14 Nov 2022 • Yong-Lu Li, Hongwei Fan, Zuoyu Qiu, Yiming Dou, Liang Xu, Hao-Shu Fang, Peiyang Guo, Haisheng Su, Dongliang Wang, Wei Wu, Cewu Lu
In daily HOIs, humans often interact with a variety of objects, e. g., holding and touching dozens of household items in cleaning.
8 code implementations • 7 Nov 2022 • Hao-Shu Fang, Jiefeng Li, Hongyang Tang, Chao Xu, Haoyi Zhu, Yuliang Xiu, Yong-Lu Li, Cewu Lu
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision.
1 code implementation • 4 Aug 2022 • Yue Xu, Yong-Lu Li, Jiefeng Li, Cewu Lu
Previous methods tackle with data imbalance from the viewpoints of data distribution, feature space, and model design, etc.
1 code implementation • 28 Jul 2022 • Xiaoqian Wu, Yong-Lu Li, Xinpeng Liu, Junyi Zhang, Yuzhe Wu, Cewu Lu
Though significant progress has been made, interactiveness learning remains a challenging problem in HOI detection: existing methods usually generate redundant negative H-O pair proposals and fail to effectively extract interactive pairs.
Ranked #9 on Human-Object Interaction Detection on V-COCO
1 code implementation • CVPR 2022 • Xinpeng Liu, Yong-Lu Li, Xiaoqian Wu, Yu-Wing Tai, Cewu Lu, Chi-Keung Tang
Human-Object Interaction (HOI) detection plays a core role in activity understanding.
1 code implementation • CVPR 2022 • Xinyu Xu, Yong-Lu Li, Cewu Lu
Anticipating future events is an essential feature for intelligent systems and embodied AI.
1 code implementation • 19 Feb 2022 • Xinpeng Liu, Yong-Lu Li, Cewu Lu
To achieve OC-immunity, we propose an OC-immune network that decouples the inputs from OC, extracts OC-immune representations, and leverages uncertainty quantification to generalize to unseen objects.
3 code implementations • 14 Feb 2022 • Yong-Lu Li, Xinpeng Liu, Xiaoqian Wu, Yizhuo Li, Zuoyu Qiu, Liang Xu, Yue Xu, Hao-Shu Fang, Cewu Lu
Human activity understanding is of widespread interest in artificial intelligence and spans diverse applications like health care and behavior analysis.
no code implementations • CVPR 2022 • Jianhua Sun, YuXuan Li, Liang Chai, Hao-Shu Fang, Yong-Lu Li, Cewu Lu
Human trajectory prediction task aims to analyze human future movements given their past status, which is a crucial step for many autonomous systems such as self-driving cars and social robots.
1 code implementation • NeurIPS 2021 • Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-Lu Li, Cewu Lu
In this work, we propose sampling-argmax, a differentiable training method that imposes implicit constraints to the shape of the probability map by minimizing the expectation of the localization error.
Ranked #171 on 3D Human Pose Estimation on Human3.6M
1 code implementation • 9 Oct 2021 • Yong-Lu Li, Yue Xu, Xinyu Xu, Xiaohan Mao, Cewu Lu
To model the compositional nature of these concepts, it is a good choice to learn them as transformations, e. g., coupling and decoupling.
1 code implementation • 25 Jan 2021 • Yong-Lu Li, Xinpeng Liu, Xiaoqian Wu, Xijie Huang, Liang Xu, Cewu Lu
Human-Object Interaction (HOI) detection is an important problem to understand how humans interact with objects.
Ranked #28 on Human-Object Interaction Detection on V-COCO
1 code implementation • CVPR 2022 • Yang You, Wenhai Liu, Yanjie Ze, Yong-Lu Li, Weiming Wang, Cewu Lu
Keypoint detection is an essential component for the object registration and alignment.
1 code implementation • CVPR 2022 • Yang You, Zelin Ye, Yujing Lou, Chengkun Li, Yong-Lu Li, Lizhuang Ma, Weiming Wang, Cewu Lu
In the work, we disentangle the direct offset into Local Canonical Coordinates (LCC), box scales and box orientations.
2 code implementations • NeurIPS 2020 • Yong-Lu Li, Xinpeng Liu, Xiaoqian Wu, Yizhuo Li, Cewu Lu
Meanwhile, isolated human and object can also be integrated into coherent HOI again.
Ranked #20 on Human-Object Interaction Detection on V-COCO
no code implementations • 2 Oct 2020 • Yichen Xie, Hao-Shu Fang, Dian Shao, Yong-Lu Li, Cewu Lu
Human-object interaction (HOI) detection requires a large amount of annotated data.
Ranked #75 on Domain Generalization on PACS
1 code implementation • CVPR 2020 • Yong-Lu Li, Xinpeng Liu, Han Lu, Shiyi Wang, Junqi Liu, Jiefeng Li, Cewu Lu
In light of these, we propose a detailed 2D-3D joint representation learning method.
Ranked #1 on Human-Object Interaction Detection on Ambiguious-HOI
2 code implementations • CVPR 2020 • Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Shiyi Wang, Hao-Shu Fang, Ze Ma, Mingyang Chen, Cewu Lu
In light of this, we propose a new path: infer human part states first and then reason out the activities based on part-level semantics.
Ranked #3 on Human-Object Interaction Detection on HICO
1 code implementation • CVPR 2020 • Yong-Lu Li, Yue Xu, Xiaohan Mao, Cewu Lu
To model the compositional nature of these general concepts, it is a good choice to learn them through transformations, such as coupling and decoupling.
Ranked #1 on Compositional Zero-Shot Learning on MIT-States (Top-1 accuracy % metric)
3 code implementations • ICCV 2019 • Hao-Shu Fang, Jianhua Sun, Runzhong Wang, Minghao Gou, Yong-Lu Li, Cewu Lu
With the guidance of such map, we boost the performance of R101-Mask R-CNN on instance segmentation from 35. 7 mAP to 37. 9 mAP without modifying the backbone or network structure.
Ranked #78 on Instance Segmentation on COCO test-dev
4 code implementations • 13 Apr 2019 • Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Mingyang Chen, Ze Ma, Shiyi Wang, Hao-Shu Fang, Cewu Lu
To address these and promote the activity understanding, we build a large-scale Human Activity Knowledge Engine (HAKE) based on the human body part states.
Ranked #2 on Human-Object Interaction Detection on HICO (using extra training data)
3 code implementations • CVPR 2019 • Yong-Lu Li, Siyuan Zhou, Xijie Huang, Liang Xu, Ze Ma, Hao-Shu Fang, Yan-Feng Wang, Cewu Lu
On account of the generalization of interactiveness, interactiveness network is a transferable knowledge learner and can be cooperated with any HOI detection models to achieve desirable results.
Ranked #29 on Human-Object Interaction Detection on V-COCO