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20192026
most citedRobust Monocular Depth Estimation under Challenging Conditions

68 citations · 175 across the 16 of their papers we have counts for

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Showing 2025 · cs.CVShow all

5 papers · 2 filters

cs.CV2025

SING3R-SLAM: Submap-based Indoor Monocular Gaussian SLAM with 3D Reconstruction Priors

Kunyi Li, Michael Niemeyer, Sen Wang +3

Recent advances in dense 3D reconstruction have demonstrated strong capability in accurately capturing local geometry. However, extending these methods to incremental global recons…

cs.CV2025

Visibility-Aware Language Aggregation for Open-Vocabulary Segmentation in 3D Gaussian Splatting

Sen Wang, Kunyi Li, Siyun Liang +4

Recently, distilling open-vocabulary language features from 2D images into 3D Gaussians has attracted significant attention. Although existing methods achieve impressive language-b…

cs.CV2025

GALA: Guided Attention with Language Alignment for Open Vocabulary Gaussian Splatting

Elena Alegret, Kunyi Li, Sen Wang +5

3D scene reconstruction and understanding have gained increasing popularity, yet existing methods still struggle to capture fine-grained, language-aware 3D representations from 2D…

cs.CV2025

Prior2Former -- Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation

Sebastian Schmidt, Julius Körner, Dominik Fuchsgruber +3

In panoptic segmentation, individual instances must be separated within semantic classes. As state-of-the-art methods rely on a pre-defined set of classes, they struggle with novel…

cs.CV2025

From Open-Vocabulary to Vocabulary-Free Semantic Segmentation

Klara Reichard, Giulia Rizzoli, Stefano Gasperini +4

Open-vocabulary semantic segmentation enables models to identify novel object categories beyond their training data. While this flexibility represents a significant advancement, cu…