11 citations · 17 across the 5 of their papers we have counts for
6 papers
V-ReasonBench: Toward Unified Reasoning Benchmark Suite for Video Generation Models
Yang Luo, Xuanlei Zhao, Baijiong Lin +7
Recent progress in generative video models, such as Veo-3, has shown surprising zero-shot reasoning abilities, creating a growing need for systematic and reliable evaluation. We in…
On Geometry-Enhanced Parameter-Efficient Fine-Tuning for 3D Scene Segmentation
Liyao Tang, Zhe Chen, Dacheng Tao
The emergence of large-scale pre-trained point cloud models has significantly advanced 3D scene understanding, but adapting these models to specific downstream tasks typically dema…
Towards Modality-agnostic Label-efficient Segmentation with Entropy-Regularized Distribution Alignment
Liyao Tang, Zhe Chen, Shanshan Zhao +2
Label-efficient segmentation aims to perform effective segmentation on input data using only sparse and limited ground-truth labels for training. This topic is widely studied in 3D…
Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation
Yiyang Chen, Shanshan Zhao, Changxing Ding +3
In recent years, cross-modal domain adaptation has been studied on the paired 2D image and 3D LiDAR data to ease the labeling costs for 3D LiDAR semantic segmentation (3DLSS) in th…
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation
Liyao Tang, Zhe Chen, Shanshan Zhao +2
Pseudo-labels are widely employed in weakly supervised 3D segmentation tasks where only sparse ground-truth labels are available for learning. Existing methods often rely on empiri…
Contrastive Boundary Learning for Point Cloud Segmentation
Liyao Tang, Yibing Zhan, Zhe Chen +2
Point cloud segmentation is fundamental in understanding 3D environments. However, current 3D point cloud segmentation methods usually perform poorly on scene boundaries, which deg…