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20242026
most citedNEBULA: Do We Evaluate Vision-Language-Action Agents Correctly?

1 citations · 1 across the 11 of their papers we have counts for

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cs.CV2026

Filling the Unseen: Scene Extrapolation via 3D Gaussian Splatting

Yunlai Zhou, Yiren Lu, Tuo Liang +3

3D Gaussian Splatting achieves photorealistic reconstruction within training view distribution, yet it degrades on out-of-distribution novel views, exhibiting holes in unobserved r…

cs.CV2025

BARD-GS: Blur-Aware Reconstruction of Dynamic Scenes via Gaussian Splatting

Yiren Lu, Yunlai Zhou, Disheng Liu +2

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the q…

cs.CV2025

When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning?

Tuo Liang, Zhe Hu, Jing Li +8

Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant challenge for large vision-language mod…

cs.CV2025

Segment then Splat: Unified 3D Open-Vocabulary Segmentation via Gaussian Splatting

Yiren Lu, Yunlai Zhou, Yiran Qiao +5

Open-vocabulary querying in 3D space is crucial for enabling more intelligent perception in applications such as robotics, autonomous systems, and augmented reality. However, most…

cs.CV2025

CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data

Disheng Liu, Yiran Qiao, Wuche Liu +5

True intelligence hinges on the ability to uncover and leverage hidden causal relations. Despite significant progress in AI and computer vision (CV), there remains a lack of benchm…