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Honggyu An

7 accepted papers

2026

Emergent Outlier View Rejection in Visual Geometry Grounded Transformers

CVPR 2026

Reliable 3D reconstruction from in-the-wild image collections is often hindered by noisy images--irrelevant inputs with little or no view overlap with others. While traditional Structure-from-Motion pipelines handle such cases through geometric verification and outlier rejection, feed-forward 3D rec

Cited by 0SourcecodeScholar
2026

Learning Compact 3D Representations from Feed-Forward Novel View Synthesis

CVPR 2026

Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. Recent approaches use per-pixel 3D Gaussian Splatting for reconstruction, followed by a 2D-to-3D feature lifting stage for scene understanding. However,

Cited by 0SourcecodeScholar
2025

Cross-View Completion Models are Zero-shot Correspondence Estimators

CVPR 2025highlight

In this work, we analyze new aspects of cross-view completion, mainly through the analogy of cross-view completion and traditional self-supervised correspondence learning algorithms. Based on our analysis, we reveal that the cross-attention map of Croco-v2, best reflects this correspondence informat…

Cited by 2SourcePDFScholar
2025

Enhancing 3D Reconstruction for Dynamic Scenes

NeurIPS 2025poster

In this work, we address the task of 3D reconstruction in dynamic scenes, where object motions frequently degrade the quality of previous 3D pointmap regression methods, such as DUSt3R, that are originally designed for static 3D scene reconstruction. Although these methods provide an elegant and pow…

Cited by 0SourceScholar
2024

Local All-Pair Correspondence for Point Tracking

ECCV 2024poster

"We introduce , a highly accurate and efficient model designed for the task of tracking any point (TAP) across video sequences. Previous approaches in this task often rely on local 2D correlation maps to establish correspondences from a point in the query image to a local region in the target image,…

2024

MaskingDepth: Masked Consistency Regularization for Semi-Supervised Monocular Depth Estimation

IROS 2024poster

We propose MaskingDepth, a semi-supervised learning framework for monocular depth estimation. MaskingDepth is designed to enforce consistency between the depths obtained from strongly-augmented images and the pseudo-depths derived from weakly-augmented images, which enables mitigating the reliance o…

Cited by 0SourcecodeScholar
2023

DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation

NeurIPS 2023poster

Neural radiance field (NeRF) shows powerful performance in novel view synthesis and 3D geometry reconstruction, but it suffers from critical performance degradation when the number of known viewpoints is drastically reduced. Existing works attempt to overcome this problem by employing external prior…

Cited by 18SourcePDFScholar