8 papers
Teeth2Point: A Two-Stage Dental CBCT ROI-to-Point Segmentation Framework
Qi Ma, Shipra Jain, Niko Benjamin Huber +1
Modern deep learning architectures have demonstrated strong performance in dental CBCT segmentation. One remaining crucial challenge is accurate tooth labeling in cases with missin…
Gaussian-JEPA: Joint-Embedding Predictive Learning for 3D Gaussian Splats
Bin Ren, Qi Ma, Yue Li +7
3D Gaussian Splatting (3DGS) represents 3D content with anisotropic primitives that jointly encode geometry and appearance. Fixed-budget encoders consume sampled observations of Ga…
Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding
Yue Li, Qi Ma, Runyi Yang +8
While 3DGS has emerged as a high-fidelity scene representation, encoding rich, general-purpose features directly from its primitives remains under-explored. We address this gap by…
ORSIFlow: Saliency-Guided Rectified Flow for Optical Remote Sensing Salient Object Detection
Haojing Chen, Zhihang Liu, Yutong Li +3
Optical Remote Sensing Image Salient Object Detection (ORSI-SOD) remains challenging due to complex backgrounds, low contrast, irregular object shapes, and large variations in obje…
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting
Mengjiao Ma, Qi Ma, Yue Li +10
3D Gaussian Splatting (3DGS) serves as a highly performant and efficient encoding of scene geometry, appearance, and semantics. Moreover, grounding language in 3D scenes has proven…
ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining
Qi Ma, Yue Li, Bin Ren +5
3D Gaussian Splatting (3DGS) has become the de facto method of 3D representation in many vision tasks. This calls for the 3D understanding directly in this representation space. To…