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Daniel Rho

7 accepted papers

2025

NFL-BA: Near-Field Light Bundle Adjustment for SLAM in Dynamic Lighting

NeurIPS 2025poster

Simultaneous Localization and Mapping (SLAM) systems typically assume static, distant illumination; however, many real-world scenarios, such as endoscopy, subterranean robotics, and search & rescue in collapsed environments, require agents to operate with a co-located light and camera in the absence…

Cited by 0SourceScholar
2024

Compact 3D Gaussian Representation for Radiance Field

CVPR 2024highlight

Neural Radiance Fields (NeRFs) have demonstrated remarkable potential in capturing complex 3D scenes with high fidelity. However one persistent challenge that hinders the widespread adoption of NeRFs is the computational bottleneck due to the volumetric rendering. On the other hand 3D Gaussian splat…

2024

Coordinate-Aware Modulation for Neural Fields

ICLR 2024spotlight

Neural fields, mapping low-dimensional input coordinates to corresponding signals, have shown promising results in representing various signals. Numerous methodologies have been proposed, and techniques employing MLPs and grid representations have achieved substantial success. MLPs allow compact and…

2023

Masked Wavelet Representation for Compact Neural Radiance Fields

CVPR 2023poster

Neural radiance fields (NeRF) have demonstrated the potential of coordinate-based neural representation (neural fields or implicit neural representation) in neural rendering. However, using a multi-layer perceptron (MLP) to represent a 3D scene or object requires enormous computational resources and…

2023

Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields

NeurIPS 2023poster

Despite the remarkable achievements of neural radiance fields (NeRF) in representing 3D scenes and generating novel view images, the aliasing issue, rendering 'jaggies' or 'blurry' images at varying camera distances, remains unresolved in most existing approaches. The recently proposed mip-NeRF has…

Cited by 10SourcePDFScholar
2023

Regression to Classification: Waveform Encoding for Neural Field-Based Audio Signal Representation

ICASSP 2023accepted

Neural fields, also known as coordinate-based representations, are an emerging signal representation framework. This approach has also been used to represent audio signals, but the generated audio often contains noise. To reduce noise and improve representation quality, we propose using waveform enc…

Cited by 0SourceScholar