Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Liu, Qihao"'
Autor:
Ma, Wufei, Zeng, Guanning, Zhang, Guofeng, Liu, Qihao, Zhang, Letian, Kortylewski, Adam, Liu, Yaoyao, Yuille, Alan
A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D (e.g., class name and bounding box) and 3D information (e.g., 3D location and 3D viewpoint) for arbitrary rigid objects in natural images. This i
Externí odkaz:
http://arxiv.org/abs/2406.09613
This paper presents innovative enhancements to diffusion models by integrating a novel multi-resolution network and time-dependent layer normalization. Diffusion models have gained prominence for their effectiveness in high-fidelity image generation.
Externí odkaz:
http://arxiv.org/abs/2406.09416
We present DIRECT-3D, a diffusion-based 3D generative model for creating high-quality 3D assets (represented by Neural Radiance Fields) from text prompts. Unlike recent 3D generative models that rely on clean and well-aligned 3D data, limiting them t
Externí odkaz:
http://arxiv.org/abs/2406.04322
Autor:
Wang, Qian, Liu, Yaoyao, Ling, Hefei, Li, Yingwei, Liu, Qihao, Li, Ping, Chen, Jiazhong, Yuille, Alan, Yu, Ning
In response to the rapidly evolving nature of adversarial attacks against visual classifiers on a monthly basis, numerous defenses have been proposed to generalize against as many known attacks as possible. However, designing a defense method that ge
Externí odkaz:
http://arxiv.org/abs/2312.09481
We present GLEE in this work, an object-level foundation model for locating and identifying objects in images and videos. Through a unified framework, GLEE accomplishes detection, segmentation, tracking, grounding, and identification of arbitrary obj
Externí odkaz:
http://arxiv.org/abs/2312.09158
Autor:
Xu, Jiacong, Zhang, Yi, Peng, Jiawei, Ma, Wufei, Jesslen, Artur, Ji, Pengliang, Hu, Qixin, Zhang, Jiehua, Liu, Qihao, Wang, Jiahao, Ji, Wei, Wang, Chen, Yuan, Xiaoding, Kaushik, Prakhar, Zhang, Guofeng, Liu, Jie, Xie, Yushan, Cui, Yawen, Yuille, Alan, Kortylewski, Adam
Accurately estimating the 3D pose and shape is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife conservation. However, research in this area is held back by the lack o
Externí odkaz:
http://arxiv.org/abs/2308.11737
Autor:
Ma, Wufei, Liu, Qihao, Wang, Jiahao, Wang, Angtian, Yuan, Xiaoding, Zhang, Yi, Xiao, Zihao, Zhang, Guofeng, Lu, Beijia, Duan, Ruxiao, Qi, Yongrui, Kortylewski, Adam, Liu, Yaoyao, Yuille, Alan
Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack explicit control over the 3D structure in the generated images. Consequ
Externí odkaz:
http://arxiv.org/abs/2306.08103
Text-guided diffusion models (TDMs) are widely applied but can fail unexpectedly. Common failures include: (i) natural-looking text prompts generating images with the wrong content, or (ii) different random samples of the latent variables that genera
Externí odkaz:
http://arxiv.org/abs/2306.00974
Despite significant efforts, cutting-edge video segmentation methods still remain sensitive to occlusion and rapid movement, due to their reliance on the appearance of objects in the form of object embeddings, which are vulnerable to these disturbanc
Externí odkaz:
http://arxiv.org/abs/2303.08132
PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation
Human pose and shape (HPS) estimation methods achieve remarkable results. However, current HPS benchmarks are mostly designed to test models in scenarios that are similar to the training data. This can lead to critical situations in real-world applic
Externí odkaz:
http://arxiv.org/abs/2303.07337