Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Ai, Wensi"'
Autor:
Ge, Yunhao, Tang, Yihe, Xu, Jiashu, Gokmen, Cem, Li, Chengshu, Ai, Wensi, Martinez, Benjamin Jose, Aydin, Arman, Anvari, Mona, Chakravarthy, Ayush K, Yu, Hong-Xing, Wong, Josiah, Srivastava, Sanjana, Lee, Sharon, Zha, Shengxin, Itti, Laurent, Li, Yunzhu, Martín-Martín, Roberto, Liu, Miao, Zhang, Pengchuan, Zhang, Ruohan, Fei-Fei, Li, Wu, Jiajun
The systematic evaluation and understanding of computer vision models under varying conditions require large amounts of data with comprehensive and customized labels, which real-world vision datasets rarely satisfy. While current synthetic data gener
Externí odkaz:
http://arxiv.org/abs/2405.09546
Autor:
Li, Chengshu, Zhang, Ruohan, Wong, Josiah, Gokmen, Cem, Srivastava, Sanjana, Martín-Martín, Roberto, Wang, Chen, Levine, Gabrael, Ai, Wensi, Martinez, Benjamin, Yin, Hang, Lingelbach, Michael, Hwang, Minjune, Hiranaka, Ayano, Garlanka, Sujay, Aydin, Arman, Lee, Sharon, Sun, Jiankai, Anvari, Mona, Sharma, Manasi, Bansal, Dhruva, Hunter, Samuel, Kim, Kyu-Young, Lou, Alan, Matthews, Caleb R, Villa-Renteria, Ivan, Tang, Jerry Huayang, Tang, Claire, Xia, Fei, Li, Yunzhu, Savarese, Silvio, Gweon, Hyowon, Liu, C. Karen, Wu, Jiajun, Fei-Fei, Li
We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an extensive survey on "what do you want robots to do for you?". The first is the de
Externí odkaz:
http://arxiv.org/abs/2403.09227
Autor:
Dass, Shivin, Ai, Wensi, Jiang, Yuqian, Singh, Samik, Hu, Jiaheng, Zhang, Ruohan, Stone, Peter, Abbatematteo, Ben, Martín-Martín, Roberto
A critical bottleneck limiting imitation learning in robotics is the lack of data. This problem is more severe in mobile manipulation, where collecting demonstrations is harder than in stationary manipulation due to the lack of available and easy-to-
Externí odkaz:
http://arxiv.org/abs/2403.07869
Autor:
Zhang, Ruohan, Lee, Sharon, Hwang, Minjune, Hiranaka, Ayano, Wang, Chen, Ai, Wensi, Tan, Jin Jie Ryan, Gupta, Shreya, Hao, Yilun, Levine, Gabrael, Gao, Ruohan, Norcia, Anthony, Fei-Fei, Li, Wu, Jiajun
We present Neural Signal Operated Intelligent Robots (NOIR), a general-purpose, intelligent brain-robot interface system that enables humans to command robots to perform everyday activities through brain signals. Through this interface, humans commun
Externí odkaz:
http://arxiv.org/abs/2311.01454
Autor:
Gong, Ran, Huang, Jiangyong, Zhao, Yizhou, Geng, Haoran, Gao, Xiaofeng, Wu, Qingyang, Ai, Wensi, Zhou, Ziheng, Terzopoulos, Demetri, Zhu, Song-Chun, Jia, Baoxiong, Huang, Siyuan
Understanding the continuous states of objects is essential for task learning and planning in the real world. However, most existing task learning benchmarks assume discrete (e.g., binary) object goal states, which poses challenges for the learning o
Externí odkaz:
http://arxiv.org/abs/2304.04321
With the recent progress of simulations by 3D modeling software and game engines, many researchers have focused on Embodied AI tasks in the virtual environment. However, the research community lacks a platform that can easily serve both indoor scene
Externí odkaz:
http://arxiv.org/abs/2206.11887
Dramatic progress has been made in animating individual characters. However, we still lack automatic control over activities between characters, especially those involving interactions. In this paper, we present a novel energy-based framework to samp
Externí odkaz:
http://arxiv.org/abs/2203.04930
With the recent success of deep learning algorithms, many researchers have focused on generative models for human motion animation. However, the research community lacks a platform for training and benchmarking various algorithms, and the animation i
Externí odkaz:
http://arxiv.org/abs/2112.06060
In this paper, we propose a lightweight music-generating model based on variational autoencoder (VAE) with structured attention. Generating music is different from generating text because the melodies with chords give listeners distinguished polyphon
Externí odkaz:
http://arxiv.org/abs/2011.09078
Publikováno v:
Proceedings of the Annual Meeting of the Cognitive Science Society, vol 45, iss 45
We propose a novel approach that utilizes virtual reality (VR) and simulation environments to quantify the impact of visual impairments (VIs) on daily tasks, e.g., to what extent does glaucoma slow people down in wiping a table or chopping vegetables
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::d527862401dae1f242d804682055fa7c
https://escholarship.org/uc/item/2sj3r0n2
https://escholarship.org/uc/item/2sj3r0n2