Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Yang, Wenfei"'
Autor:
Lu, Jiahao, Deng, Jiacheng, Zhu, Ruijie, Liang, Yanzhe, Yang, Wenfei, Zhang, Tianzhu, Zhou, Xu
Dynamic scenes rendering is an intriguing yet challenging problem. Although current methods based on NeRF have achieved satisfactory performance, they still can not reach real-time levels. Recently, 3D Gaussian Splatting (3DGS) has garnered researche
Externí odkaz:
http://arxiv.org/abs/2410.13607
Autor:
Zhu, Ruijie, Liang, Yanzhe, Chang, Hanzhi, Deng, Jiacheng, Lu, Jiahao, Yang, Wenfei, Zhang, Tianzhu, Zhang, Yongdong
Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to dynamic sc
Externí odkaz:
http://arxiv.org/abs/2410.07707
Monocular depth estimation aims to infer a dense depth map from a single image, which is a fundamental and prevalent task in computer vision. Many previous works have shown impressive depth estimation results through carefully designed network struct
Externí odkaz:
http://arxiv.org/abs/2409.02494
Autor:
Li, Zhuoyuan, Ai, Yubo, Lu, Jiahao, Wang, ChuXin, Deng, Jiacheng, Chang, Hanzhi, Liang, Yanzhe, Yang, Wenfei, Zhang, Shifeng, Zhang, Tianzhu
Transformers have demonstrated impressive results for 3D point cloud semantic segmentation. However, the quadratic complexity of transformer makes computation cost high, limiting the number of points that can be processed simultaneously and impeding
Externí odkaz:
http://arxiv.org/abs/2406.17442
Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimation
Category-level 6D object pose estimation aims to estimate the rotation, translation and size of unseen instances within specific categories. In this area, dense correspondence-based methods have achieved leading performance. However, they do not expl
Externí odkaz:
http://arxiv.org/abs/2403.19527
Autor:
Zhu, Yu, Sun, Chuxiong, Yang, Wenfei, Wei, Wenqiang, Tang, Bo, Zhang, Tianzhu, Li, Zhiyu, Zhang, Shifeng, Xiong, Feiyu, Hu, Jie, yang, Mingchuan
Reinforcement Learning from Human Feedback (RLHF) is the prevailing approach to ensure Large Language Models (LLMs) align with human values. However, existing RLHF methods require a high computational cost, one main reason being that RLHF assigns bot
Externí odkaz:
http://arxiv.org/abs/2403.04283
Single object tracking aims to locate the target object in a video sequence according to the state specified by different modal references, including the initial bounding box (BBOX), natural language (NL), or both (NL+BBOX). Due to the gap between di
Externí odkaz:
http://arxiv.org/abs/2401.11228
Autor:
Xie, Xianghui, Wang, Xi, Athanasiou, Nikos, Bhatnagar, Bharat Lal, Huang, Chun-Hao P., Mo, Kaichun, Chen, Hao, Jia, Xia, Zhang, Zerui, Cui, Liangxian, Lin, Xiao, Qian, Bingqiao, Xiao, Jie, Yang, Wenfei, Nam, Hyeongjin, Jung, Daniel Sungho, Kim, Kihoon, Lee, Kyoung Mu, Hilliges, Otmar, Pons-Moll, Gerard
Modeling the interaction between humans and objects has been an emerging research direction in recent years. Capturing human-object interaction is however a very challenging task due to heavy occlusion and complex dynamics, which requires understandi
Externí odkaz:
http://arxiv.org/abs/2401.04143
Not Every Side Is Equal: Localization Uncertainty Estimation for Semi-Supervised 3D Object Detection
Semi-supervised 3D object detection from point cloud aims to train a detector with a small number of labeled data and a large number of unlabeled data. The core of existing methods lies in how to select high-quality pseudo-labels using the designed q
Externí odkaz:
http://arxiv.org/abs/2312.10390
Weakly-supervised temporal action localization aims to localize and recognize actions in untrimmed videos with only video-level category labels during training. Without instance-level annotations, most existing methods follow the Segment-based Multip
Externí odkaz:
http://arxiv.org/abs/2305.17861