enterprise
发表于 2025-3-28 16:55:41
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abnegate
发表于 2025-3-28 19:04:48
Helena Handschuh,Anna Lysyanskayam the raw point clouds for 3D object detection, most previous researches utilize PointNet and its variants as the feature learning backbone and have seen encouraging results. However, these methods capture point features independently without modeling the interaction between points, and simple symme
钢笔记下惩罚
发表于 2025-3-29 00:23:36
Arthur Lazzaretti,Charalampos Papamanthouity of existing networks are relatively fixed, which makes it difficult for them to be flexibly applied to devices with different computational constraints. Instead of manually designing the network structure for each specific device, in this paper, we propose a novel training-free neural architectu
COW
发表于 2025-3-29 04:18:41
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blister
发表于 2025-3-29 09:27:30
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思考
发表于 2025-3-29 13:49:41
EAI-Stereo: Error Aware Iterative Network for Stereo Matchingwork which could carry more semantic information across iterations. We demonstrate the efficiency and effectiveness of our method on KITTI 2015, Middlebury, and ETH3D. At the time of writing this paper, EAI-Stereo ranks . on the Middlebury leaderboard and . on the ETH3D Stereo benchmark for 50% quan
鸣叫
发表于 2025-3-29 15:32:46
Temporal-Aware Siamese Tracker: Integrate Temporal Context for 3D Object Trackingate the tracking quality of the template so that the high-quality templates are collected to form the historical template set. Then, with the initial feature embeddings of the historical templates, the temporal feature enhancement module concatenates all template embeddings as a whole and then feeds
退潮
发表于 2025-3-29 23:04:09
Neural Plenoptic Sampling: Learning Light-Field from Thousands of Imaginary Eyesic function at every position in the space of interest. By placing virtual viewpoints (dubbed ‘imaginary eyes’) at thousands of randomly sampled locations and leveraging multi-view geometric relationship, we train the MLP to regress the plenoptic function for the space. Our network is trained on a p
救护车
发表于 2025-3-30 00:32:42
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香料
发表于 2025-3-30 06:32:17
NEO-3DF: Novel Editing-Oriented 3D Face Creation and Reconstruction with the original 2D image. Experiments show that the results of NEO-3DF outperform existing methods in intuitive face editing and have better 3D-to-2D alignment accuracy (14% higher IoU) than global face model-based reconstruction. Code available at ..