Zobrazeno 1 - 10
of 63
pro vyhledávání: '"HAN Wencheng"'
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 5, Pp 142-152 (2024)
CO2 capture， utilization， and storage （CCUS） can achieve a win-win situation of carbon emission reduction and oil production increase， and it is a key technology for the green and low-carbon transformation of the fossil energy industry. The
Externí odkaz:
https://doaj.org/article/a638c6feb2d94c2fa73269422d0888b8
Recent advancements in sRGB-to-RAW de-rendering have increasingly emphasized metadata-driven approaches to reconstruct RAW data from sRGB images, supplemented by partial RAW information. In image-based de-rendering, metadata is commonly obtained thro
Externí odkaz:
http://arxiv.org/abs/2411.11717
Autor:
Yan, Tianyi, Wu, Dongming, Han, Wencheng, Jiang, Junpeng, Zhou, Xia, Zhan, Kun, Xu, Cheng-zhong, Shen, Jianbing
Autonomous driving evaluation requires simulation environments that closely replicate actual road conditions, including real-world sensory data and responsive feedback loops. However, many existing simulations need to predict waypoints along fixed ro
Externí odkaz:
http://arxiv.org/abs/2411.11252
Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce high-fidelity
Externí odkaz:
http://arxiv.org/abs/2411.10369
Autor:
Chen, Dubing, Fang, Jin, Han, Wencheng, Cheng, Xinjing, Yin, Junbo, Xu, Chenzhong, Khan, Fahad Shahbaz, Shen, Jianbing
Vision-based semantic occupancy and flow prediction plays a crucial role in providing spatiotemporal cues for real-world tasks, such as autonomous driving. Existing methods prioritize higher accuracy to cater to the demands of these tasks. In this wo
Externí odkaz:
http://arxiv.org/abs/2411.07725
Recovering high-quality depth maps from compressed sources has gained significant attention due to the limitations of consumer-grade depth cameras and the bandwidth restrictions during data transmission. However, current methods still suffer from two
Externí odkaz:
http://arxiv.org/abs/2411.03239
Autor:
Han, Wencheng, Shen, Jianbing
In the area of self-supervised monocular depth estimation, models that utilize rich-resource inputs, such as high-resolution and multi-frame inputs, typically achieve better performance than models that use ordinary single image input. However, these
Externí odkaz:
http://arxiv.org/abs/2408.00361
Concurrent processing of multiple autonomous driving 3D perception tasks within the same spatiotemporal scene poses a significant challenge, in particular due to the computational inefficiencies and feature competition between tasks when using tradit
Externí odkaz:
http://arxiv.org/abs/2407.10876
In this technical report, we present our solution for the Vision-Centric 3D Occupancy and Flow Prediction track in the nuScenes Open-Occ Dataset Challenge at CVPR 2024. Our innovative approach involves a dual-stage framework that enhances 3D occupanc
Externí odkaz:
http://arxiv.org/abs/2407.01436
Publikováno v:
Open Geosciences, Vol 11, Iss 1, Pp 948-960 (2019)
Shale, a heterogeneous and extremely complex gas reservoir, contains low porosity and ultra-Low permeability properties at different pore scales. Its flow behaviors are more complicated due to different forms of flow regimes under laboratory conditio
Externí odkaz:
https://doaj.org/article/502a9733eceb48e7a2f2704732ea00ab