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Found 6 papers, 4 papers with code
Robust Point Cloud Segmentation with Noisy Annotations
To handle boundary-level label noise, we also propose a variant ``PNAL-boundary " with a progressive boundary label cleaning strategy.
Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles
Through our analysis, we find one important reason is that existing large-scale VL datasets do not contain much commonsense knowledge, which motivates us to improve the commonsense of VL-models from the data perspective.
3D Question Answering
To this end, we propose a novel transformer-based 3DQA framework "3DQA-TR", which consists of two encoders for exploiting the appearance and geometry information, respectively.
Learning with Noisy Labels for Robust Point Cloud Segmentation
Point cloud segmentation is a fundamental task in 3D.
Exemplar-Based 3D Portrait Stylization
In the second texture style transfer stage, we focus on performing style transfer on the canonical texture by adopting a differentiable renderer to optimize the texture in a multi-view framework.
Meta-PU: An Arbitrary-Scale Upsampling Network for Point Cloud
Thus, Meta-PU even outperforms the existing methods trained for a specific scale factor only.
Graphics
