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Gerhard Petrus Hancke

9 accepted papers

2026

GenSplat: Bridging the Generalization Gap in 3DGS Language Comprehension

CVPR 2026

In this paper, we propose GenSplat, a novel approach for language comprehension in 3D Gaussian Splatting (3DGS). Unlike previous methods that either achieve cross-scene generalization by being bounded to a predefined vocabulary or handle free-form language by overfitting to individual scenes, GenSpl

Cited by 0SourcecodeScholar
2025

Language-Guided Salient Object Ranking

CVPR 2025poster

Salient Object Ranking (SOR) aims to study human attention shifts across different objects in the scene. It is a challenging task, as it requires comprehension of the relations among the salient objects in the scene. However, existing works often overlook such relations or model them implicitly. In…

Cited by 0SourcePDFScholar
2025

Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion

ICLR 2025poster

Generative 3D modeling has made significant advances recently, but it remains constrained by its inherently ill-posed nature, leading to challenges in quality and controllability. Inspired by the real-world workflow that designers typically refer to existing 3D models when creating new ones, we prop…

Cited by 5SourcePDFScholar
2025

SEHDR: Single-Exposure HDR Novel View Synthesis via 3D Gaussian Bracketing

ICCV 2025poster

This paper presents SeHDR, a novel high dynamic range 3D Gaussian Splatting (HDR-3DGS) approach for generating HDR novel views given multi-view LDR images. Unlike existing methods that typically require the multi-view LDR input images to be captured from different exposures, which are tedious to cap…

2025

Unleashing the Potential of Multimodal LLMs for Zero-Shot Spatio-Temporal Video Grounding

NeurIPS 2025poster

Spatio-temporal video grounding (STVG) aims at localizing the spatio-temporal tube of a video, as specified by the input text query. In this paper, we utilize multimodal large language models (MLLMs) to explore a zero-shot solution in STVG. We reveal two key insights about MLLMs: (1) MLLMs tend to…

Cited by 0SourcecodeScholar
2024

Boosting Weakly Supervised Referring Image Segmentation via Progressive Comprehension

NeurIPS 2024poster

This paper explores the weakly-supervised referring image segmentation (WRIS) problem, and focuses on a challenging setup where target localization is learned directly from image-text pairs. We note that the input text description typically already contains detailed information on how to localize t…

Cited by 2SourcePDFScholar
2024

Color Shift Estimation-and-Correction for Image Enhancement

CVPR 2024poster

Images captured under sub-optimal illumination conditions may contain both over- and under-exposures. We observe that over- and over-exposed regions display opposite color tone distribution shifts which may not be easily normalized in joint modeling as they usually do not have "normal-exposed" regio…

2024

LuSh-NeRF: Lighting up and Sharpening NeRFs for Low-light Scenes

NeurIPS 2024poster

Neural Radiance Fields (NeRFs) have shown remarkable performances in producing novel-view images from high-quality scene images. However, hand-held low-light photography challenges NeRFs as the captured images may simultaneously suffer from low visibility, noise, and camera shakes. While existing Ne…