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20172026
most citedUnsupervised Contrastive Domain Adaptation for Semantic Segmentation

5 citations · 12 across the 6 of their papers we have counts for

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cs.CV2026

SPEAR: A Simulator for Photorealistic Embodied AI Research

Mike Roberts, Renhan Wang, Rushikesh Zawar +10

Interactive simulators have become powerful tools for training embodied agents and generating synthetic visual data, but existing photorealistic simulators suffer from limited gene…

cs.CV20251 cited

Sharp Monocular View Synthesis in Less Than a Second

Lars Mescheder, Wei Dong, Shiwei Li +10

We present SHARP, an approach to photorealistic view synthesis from a single image. Given a single photograph, SHARP regresses the parameters of a 3D Gaussian representation of the…

cs.CV2025

CoMotion: Concurrent Multi-person 3D Motion

Alejandro Newell, Peiyun Hu, Lahav Lipson +2

We introduce an approach for detecting and tracking detailed 3D poses of multiple people from a single monocular camera stream. Our system maintains temporally coherent predictions…

cs.CV202418 cited

Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Aleksei Bochkovskii, Amaël Delaunoy, Hugo Germain +4

We present a foundation model for zero-shot metric monocular depth estimation. Our model, Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high-fre…

cs.CV20242 cited

Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object Relighting

Benjamin Ummenhofer, Sanskar Agrawal, Rene Sepulveda +6

Reconstructing an object from photos and placing it virtually in a new environment goes beyond the standard novel view synthesis task as the appearance of the object has to not onl…

cs.CV20225 cited

Unsupervised Contrastive Domain Adaptation for Semantic Segmentation

Feihu Zhang, Vladlen Koltun, Philip Torr +2

Semantic segmentation models struggle to generalize in the presence of domain shift. In this paper, we introduce contrastive learning for feature alignment in cross-domain adaptati…