#depth estimation
5 papers match
Explainable and Resource-Efficient Spatial Reasoning in Multimodal LLMs for Decision-Critical Applications
Piyush Jain, Kousik Dasgupta, Rajarshi Roy +1
The paper introduces ByDeWay-V2, a training‑free prompting framework that adds explicit pairwise spatial predicates derived from depth estimation and open‑vocabulary object detecti…
X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras
Heng Zhou, Shuhong Liu, Yonghao He +6
X-Lens is a compact feed‑forward model that estimates metric depth in real time from a mix of calibrated fisheye and pinhole camera views using geometry‑aware calibration tokens an…
GeCo: Evaluating Geometric Consistency for Video Generation via Motion and Structure
Leslie Gu, Junhwa Hur, Charles Herrmann +4
GeCo is a geometry-based metric that detects deformation and occlusion inconsistencies in generated videos by combining residual motion and depth cues, providing dense consistency…
GHOST: Geometry-Guided Hallucination of Opaque Surface Textures
Langxu Zhao, Zuan Gu, Tianhan Gao
The paper introduces GHOST, a preprocessing framework that converts transparent regions into opaque, texture-rich images using geometry-guided hallucination, improving depth estima…
When Depth Is Better Told Than Shown: Depth-Ordinal Prompting for Vision-Language Spatial Reasoning
Quynh Vo, Phuc Dao, Cong-Duy Nguyen +1
The paper introduces Depth-Ordinal Prompting (DOP), a training‑free technique that converts monocular depth estimates into object‑level ordinal text cues, enabling vision‑language…
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