Zobrazeno 1 - 10
of 334
pro vyhledávání: '"Rehg, James M"'
Autor:
Lai, Bolin, Juefei-Xu, Felix, Liu, Miao, Dai, Xiaoliang, Mehta, Nikhil, Zhu, Chenguang, Huang, Zeyi, Rehg, James M., Lee, Sangmin, Zhang, Ning, Xiao, Tong
Text-guided image manipulation has experienced notable advancement in recent years. In order to mitigate linguistic ambiguity, few-shot learning with visual examples has been applied for instructions that are underrepresented in the training set, or
Externí odkaz:
http://arxiv.org/abs/2412.01027
Autor:
Xu, Maxwell A., Narain, Jaya, Darnell, Gregory, Hallgrimsson, Haraldur, Jeong, Hyewon, Forde, Darren, Fineman, Richard, Raghuram, Karthik J., Rehg, James M., Ren, Shirley
We present RelCon, a novel self-supervised *Rel*ative *Con*trastive learning approach that uses a learnable distance measure in combination with a softened contrastive loss for training an motion foundation model from wearable sensors. The learnable
Externí odkaz:
http://arxiv.org/abs/2411.18822
Autor:
Ozden, Tarik Can, Kara, Ozgur, Akcin, Oguzhan, Zaman, Kerem, Srivastava, Shashank, Chinchali, Sandeep P., Rehg, James M.
Current image immunization defense techniques against diffusion-based editing embed imperceptible noise in target images to disrupt editing models. However, these methods face scalability challenges, as they require time-consuming re-optimization for
Externí odkaz:
http://arxiv.org/abs/2411.17957
Symmetry is a ubiquitous and fundamental property in the visual world, serving as a critical cue for perception and structure interpretation. This paper investigates the detection of 3D reflection symmetry from a single RGB image, and reveals its sig
Externí odkaz:
http://arxiv.org/abs/2411.17763
Autor:
Cao, Xu, Liang, Kaizhao, Liao, Kuei-Da, Gao, Tianren, Ye, Wenqian, Chen, Jintai, Ding, Zhiguang, Cao, Jianguo, Rehg, James M., Sun, Jimeng
Modeling disease progression is crucial for improving the quality and efficacy of clinical diagnosis and prognosis, but it is often hindered by a lack of longitudinal medical image monitoring for individual patients. To address this challenge, we pro
Externí odkaz:
http://arxiv.org/abs/2411.11943
Autor:
Lai, Bolin, Toyer, Sam, Nagarajan, Tushar, Girdhar, Rohit, Zha, Shengxin, Rehg, James M., Kitani, Kris, Grauman, Kristen, Desai, Ruta, Liu, Miao
Predicting future human behavior is an increasingly popular topic in computer vision, driven by the interest in applications such as autonomous vehicles, digital assistants and human-robot interactions. The literature on behavior prediction spans var
Externí odkaz:
http://arxiv.org/abs/2410.14045
Autor:
Boote, Bikram, Thai, Anh, Jia, Wenqi, Kara, Ozgur, Stojanov, Stefan, Rehg, James M., Lee, Sangmin
Point tracking is a fundamental problem in computer vision with numerous applications in AR and robotics. A common failure mode in long-term point tracking occurs when the predicted point leaves the object it belongs to and lands on the background or
Externí odkaz:
http://arxiv.org/abs/2409.05786
Autor:
Lee, Sangmin, Li, Minzhi, Lai, Bolin, Jia, Wenqi, Ryan, Fiona, Cao, Xu, Kara, Ozgur, Boote, Bikram, Shi, Weiyan, Yang, Diyi, Rehg, James M.
Social interactions form the foundation of human societies. Artificial intelligence has made significant progress in certain areas, but enabling machines to seamlessly understand social interactions remains an open challenge. It is important to addre
Externí odkaz:
http://arxiv.org/abs/2409.15316
3D object part segmentation is essential in computer vision applications. While substantial progress has been made in 2D object part segmentation, the 3D counterpart has received less attention, in part due to the scarcity of annotated 3D datasets, w
Externí odkaz:
http://arxiv.org/abs/2407.09648
Autor:
Wei, Hui, Xu, Maxwell A., Samplawski, Colin, Rehg, James M., Kumar, Santosh, Marlin, Benjamin M.
Wearable sensors enable health researchers to continuously collect data pertaining to the physiological state of individuals in real-world settings. However, such data can be subject to extensive missingness due to a complex combination of factors. I
Externí odkaz:
http://arxiv.org/abs/2406.18848