3 citations · 5 across the 5 of their papers we have counts for
6 papers · 1 filter
Semantic Occupancy Prediction with Dual Range-Voxel Representation
Sitao Chen, Zhuangwei Zhuang, Hui Luo +3
LiDAR-based 3D semantic occupancy prediction, which aims to provide accurate and comprehensive scene representation, is crucial for autonomous driving systems. As point clouds suff…
Robust 3D Semantic Occupancy Prediction with Calibration-free Spatial Transformation
Zhuangwei Zhuang, Ziyin Wang, Sitao Chen +3
3D semantic occupancy prediction, which seeks to provide accurate and comprehensive representations of environment scenes, is important to autonomous driving systems. For autonomou…
Contrastive Vision-Language Alignment Makes Efficient Instruction Learner
Lizhao Liu, Xinyu Sun, Tianhang Xiang +3
We study the task of extending the large language model (LLM) into a vision-language instruction-following model. This task is crucial but challenging since the LLM is trained on t…
CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation
Lizhao Liu, Zhuangwei Zhuang, Shangxin Huang +5
We study the task of weakly-supervised point cloud semantic segmentation with sparse annotations (e.g., less than 0.1% points are labeled), aiming to reduce the expensive cost of d…
Instance Segmentation for Chinese Character Stroke Extraction, Datasets and Benchmarks
Lizhao Liu, Kunyang Lin, Shangxin Huang +4
Stroke is the basic element of Chinese character and stroke extraction has been an important and long-standing endeavor. Existing stroke extraction methods are often handcrafted an…
DAS: Densely-Anchored Sampling for Deep Metric Learning
Lizhao Liu, Shangxin Huang, Zhuangwei Zhuang +3
Deep Metric Learning (DML) serves to learn an embedding function to project semantically similar data into nearby embedding space and plays a vital role in many applications, such…