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Ruikang Xu

11 accepted papers

2026

Arbitrary-Shaped Image Generation via Spherical Neural Field Diffusion

ICLR 2026poster

Existing diffusion models excel at generating diverse content, but remain confined to fixed image shapes and lack the ability to flexibly control spatial attributes such as viewpoint, field-of-view (FOV), and resolution. To fill this gap, we propose Arbitrary-Shaped Image Generation (ASIG), the fir…

Cited by 0SourceScholar
2026

FastGaMer: Efficient GainMap Learning for Practical Inverse Tone Mapping

CVPR 2026

Inverse tone mapping (ITM) becomes significantly harder when the SDR input is produced by local tone mapping, which jointly applies global radiometric compression and spatially varying adaptations that distort dynamic range, contrast, and channel-wise color ratios. Existing ITM methods ignore this d

Cited by 0SourceScholar
2026

MarCon: Max-Margin Contrastive Learning for Imbalanced Domain Adaptation Semantic Segmentation

IJCAI 2026

Unsupervised Domain Adaptation for Semantic Segmentation (UDA-SS) has seen significant progress in recent years. Existing UDA-SS approaches mostly adopt a pseudo-labeling schema to adapt model in the target domain, but they often overlook the inherent long-tailed data distribution in segmentation. W

Cited by 0Scholar
2026

RawMetaDiff: Unlocking Extreme Darkness from Dual-Exposure RAW with Meta-Guided Diffusion

CVPR 2026

Extreme low-light Raw image restoration remains challenging due to overwhelming noise and severe detail loss.In this paper, we exploit the potential of the dual-exposure setting for this severely ill-posed problem.Existing methods suffer from unreliable cross-exposure alignment, resulting in degrade

Cited by 0SourceScholar
2025

Event-boosted Deformable 3D Gaussians for Dynamic Scene Reconstruction

ICCV 2025poster

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture high-temporal-resolution, continuous motion data, with deformable…

2025

HDR Image Generation via Gain Map Decomposed Diffusion

ICCV 2025poster

While diffusion models have demonstrated significant success in standard dynamic range (SDR) image synthesis, generating high dynamic range (HDR) images with higher luminance and broader color gamuts remains challenging. This arises primarily from two factors: (1) The incompatibility between pretrai…

2025

Learning Gain Map for Inverse Tone Mapping

ICLR 2025poster

For a more compatible and consistent high dynamic range (HDR) viewing experience, a new image format with a double-layer structure has been developed recently, which incorporates an auxiliary Gain Map (GM) within a standard dynamic range (SDR) image for adaptive HDR display. This new format motivate…

2024

High-Resolution and Few-shot View Synthesis from Asymmetric Dual-lens Inputs

ECCV 2024poster

"Novel view synthesis has achieved remarkable quality and efficiency by the paradigm of 3D Gaussian Splatting (3D-GS), but still faces two challenges: 1) significant performance degradation when trained with only few-shot samples due to a lack of geometry constraint, and 2) incapability of rendering…

2023

Generalized Lightness Adaptation with Channel Selective Normalization

ICCV 2023poster

Lightness adaptation is vital to the success of image processing to avoid unexpected visual deterioration, which covers multiple aspects, e.g., low-light image enhancement, image retouching, and inverse tone mapping. Existing methods typically work well on their trained lightness conditions but perf…

Cited by 20PDFcodeScholar
2023

Toward RAW Object Detection: A New Benchmark and a New Model

CVPR 2023poster

In many computer vision applications (e.g., robotics and autonomous driving), high dynamic range (HDR) data is necessary for object detection algorithms to handle a variety of lighting conditions, such as strong glare. In this paper, we aim to achieve object detection on RAW sensor data, which natur…

Cited by 28SourcePDFScholar