Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Wang, Shenlong"'
Autor:
Shen, Yuan, Ceylan, Duygu, Guerrero, Paul, Xu, Zexiang, Mitra, Niloy J., Wang, Shenlong, Frühstück, Anna
We present a simple, modular, and generic method that upsamples coarse 3D models by adding geometric and appearance details. While generative 3D models now exist, they do not yet match the quality of their counterparts in image and video domains. We
Externí odkaz:
http://arxiv.org/abs/2406.00609
Video2Game: Real-time, Interactive, Realistic and Browser-Compatible Environment from a Single Video
Creating high-quality and interactive virtual environments, such as games and simulators, often involves complex and costly manual modeling processes. In this paper, we present Video2Game, a novel approach that automatically converts videos of real-w
Externí odkaz:
http://arxiv.org/abs/2404.09833
The latest regularized Neural Radiance Field (NeRF) approaches produce poor geometry and view extrapolation for multiview stereo (MVS) benchmarks such as ETH3D. In this paper, we aim to create 3D models that provide accurate geometry and view synthes
Externí odkaz:
http://arxiv.org/abs/2404.08252
We introduce GoMAvatar, a novel approach for real-time, memory-efficient, high-quality animatable human modeling. GoMAvatar takes as input a single monocular video to create a digital avatar capable of re-articulation in new poses and real-time rende
Externí odkaz:
http://arxiv.org/abs/2404.07991
Autor:
Zhai, Albert J., Shen, Yuan, Chen, Emily Y., Wang, Gloria X., Wang, Xinlei, Wang, Sheng, Guan, Kaiyu, Wang, Shenlong
Can computers perceive the physical properties of objects solely through vision? Research in cognitive science and vision science has shown that humans excel at identifying materials and estimating their physical properties based purely on visual app
Externí odkaz:
http://arxiv.org/abs/2404.04242
We present LidarDM, a novel LiDAR generative model capable of producing realistic, layout-aware, physically plausible, and temporally coherent LiDAR videos. LidarDM stands out with two unprecedented capabilities in LiDAR generative modeling: (i) LiDA
Externí odkaz:
http://arxiv.org/abs/2404.02903
Autor:
Jiang, Hanxiao, Huang, Binghao, Wu, Ruihai, Li, Zhuoran, Garg, Shubham, Nayyeri, Hooshang, Wang, Shenlong, Li, Yunzhu
Robots need to explore their surroundings to adapt to and tackle tasks in unknown environments. Prior work has proposed building scene graphs of the environment but typically assumes that the environment is static, omitting regions that require activ
Externí odkaz:
http://arxiv.org/abs/2402.15487
Autor:
Lin, Zhi-Hao, Huang, Jia-Bin, Li, Zhengqin, Dong, Zhao, Richardt, Christian, Li, Tuotuo, Zollhöfer, Michael, Kopf, Johannes, Wang, Shenlong, Kim, Changil
While numerous 3D reconstruction and novel-view synthesis methods allow for photorealistic rendering of a scene from multi-view images easily captured with consumer cameras, they bake illumination in their representations and fall short of supporting
Externí odkaz:
http://arxiv.org/abs/2401.12977
Autor:
Ummenhofer, Benjamin, Agrawal, Sanskar, Sepulveda, Rene, Lao, Yixing, Zhang, Kai, Cheng, Tianhang, Richter, Stephan, Wang, Shenlong, Ros, German
Reconstructing an object from photos and placing it virtually in a new environment goes beyond the standard novel view synthesis task as the appearance of the object has to not only adapt to the novel viewpoint but also to the new lighting conditions
Externí odkaz:
http://arxiv.org/abs/2401.09126
Our world is full of identical objects (\emphe.g., cans of coke, cars of same model). These duplicates, when seen together, provide additional and strong cues for us to effectively reason about 3D. Inspired by this observation, we introduce Structure
Externí odkaz:
http://arxiv.org/abs/2401.05236