Zobrazeno 1 - 10
of 229
pro vyhledávání: '"MA Yuexin"'
Autor:
Yan, Ziyang, Dong, Wenzhen, Shao, Yihua, Lu, Yuhang, Haiyang, Liu, Liu, Jingwen, Wang, Haozhe, Wang, Zhe, Wang, Yan, Remondino, Fabio, Ma, Yuexin
End-to-end autonomous driving with vision-only is not only more cost-effective compared to LiDAR-vision fusion but also more reliable than traditional methods. To achieve a economical and robust purely visual autonomous driving system, we propose Ren
Externí odkaz:
http://arxiv.org/abs/2409.11356
In this paper, we propose an algorithm for registering sequential bounding boxes with point cloud streams. Unlike popular point cloud registration techniques, the alignment of the point cloud and the bounding box can rely on the properties of the bou
Externí odkaz:
http://arxiv.org/abs/2409.09312
Autor:
Dai, Yudi, Wang, Zhiyong, Lin, Xiping, Wen, Chenglu, Xu, Lan, Shen, Siqi, Ma, Yuexin, Wang, Cheng
We introduce HiSC4D, a novel Human-centered interaction and 4D Scene Capture method, aimed at accurately and efficiently creating a dynamic digital world, containing large-scale indoor-outdoor scenes, diverse human motions, rich human-human interacti
Externí odkaz:
http://arxiv.org/abs/2409.04398
Large Vision-Language Models (LVLMs) have recently garnered significant attention, with many efforts aimed at harnessing their general knowledge to enhance the interpretability and robustness of autonomous driving models. However, LVLMs typically rel
Externí odkaz:
http://arxiv.org/abs/2409.02914
Human motion prediction is crucial for human-centric multimedia understanding and interacting. Current methods typically rely on ground truth human poses as observed input, which is not practical for real-world scenarios where only raw visual sensor
Externí odkaz:
http://arxiv.org/abs/2408.08202
The reconstruction of high-quality shape geometry is crucial for developing freehand 3D ultrasound imaging. However, the shape reconstruction of multi-view ultrasound data remains challenging due to the elevation distortion caused by thick transducer
Externí odkaz:
http://arxiv.org/abs/2408.07325
We introduce Multi-Cylindrical Panoramic Depth Estimation (MCPDepth), a two-stage framework for omnidirectional depth estimation via stereo matching between multiple cylindrical panoramas. MCPDepth uses cylindrical panoramas for initial stereo matchi
Externí odkaz:
http://arxiv.org/abs/2408.01653
Modeling and capturing the 3D spatial arrangement of the human and the object is the key to perceiving 3D human-object interaction from monocular images. In this work, we propose to use the Human-Object Offset between anchors which are densely sample
Externí odkaz:
http://arxiv.org/abs/2407.20545
Unsupervised 3D instance segmentation aims to segment objects from a 3D point cloud without any annotations. Existing methods face the challenge of either too loose or too tight clustering, leading to under-segmentation or over-segmentation. To addre
Externí odkaz:
http://arxiv.org/abs/2407.10084
LiDAR-based human motion capture has garnered significant interest in recent years for its practicability in large-scale and unconstrained environments. However, most methods rely on cleanly segmented human point clouds as input, the accuracy and smo
Externí odkaz:
http://arxiv.org/abs/2407.09833