2 citations · 5 across the 5 of their papers we have counts for
5 papers
ES-MVSNet: Efficient Framework for End-to-end Self-supervised Multi-View Stereo
Qiang Zhou, Chaohui Yu, Jingliang Li +3
Compared to the multi-stage self-supervised multi-view stereo (MVS) method, the end-to-end (E2E) approach has received more attention due to its concise and efficient training pipe…
Improved Neural Radiance Fields Using Pseudo-depth and Fusion
Jingliang Li, Qiang Zhou, Chaohui Yu +4
Since the advent of Neural Radiance Fields, novel view synthesis has received tremendous attention. The existing approach for the generalization of radiance field reconstruction pr…
Points-to-3D: Bridging the Gap between Sparse Points and Shape-Controllable Text-to-3D Generation
Chaohui Yu, Qiang Zhou, Jingliang Li +3
Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on score d…
LMSeg: Language-guided Multi-dataset Segmentation
Qiang Zhou, Yuang Liu, Chaohui Yu +3
It's a meaningful and attractive topic to build a general and inclusive segmentation model that can recognize more categories in various scenarios. A straightforward way is to comb…
Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation
Chaohui Yu, Qiang Zhou, Jingliang Li +3
Modern incremental learning for semantic segmentation methods usually learn new categories based on dense annotations. Although achieve promising results, pixel-by-pixel labeling i…