# Research Radar · 2026-05-26 (Tue)

_Auto-generated daily arXiv monitoring dashboard_

## 🔬 Fine-Grained CV (5 papers)

### 1. AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond

- **arXiv:** `2605.26113` | [Abstract](https://arxiv.org/abs/2605.26113v1) | [PDF](https://arxiv.org/pdf/2605.26113v1)
- **Authors:** Haiming Zhang, Junfei Zhou, Feng Jiang, Jingzhong Li, Zhenglong Guo et al.
- **Published:** 2026-05-25

Generating high-fidelity and controllable synthetic data is critical for advancing end-to-end autonomous driving, particularly for addressing the long tail of rare safety-critical scenarios. Existing occupancy-guided methods typically rely on shallow conditioning mechanisms and reference-frame-depen

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### 2. Pixel-Level Pavement Distress Assessment Using Instance Segmentation

- **arXiv:** `2605.26095` | [Abstract](https://arxiv.org/abs/2605.26095v1) | [PDF](https://arxiv.org/pdf/2605.26095v1)
- **Authors:** Logan Dewick, Bibesh Pyakurel, Kong Pheng Yang, Nazim Choudhury, M. G. Sarwar Murshed
- **Published:** 2026-05-25

Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localization of thin, branching, and irregular cracks to achieve the geometric precision necessary for maintenance-relevant quantification. This paper presents a v

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### 3. Channel-wise Vector Quantization

- **arXiv:** `2605.26089` | [Abstract](https://arxiv.org/abs/2605.26089v1) | [PDF](https://arxiv.org/pdf/2605.26089v1)
- **Authors:** Wei Song, Tianhang Wang, Yitong Chen, Tong Zhang, Zuxuan Wu et al.
- **Published:** 2026-05-25

We present Channel-wise Vector Quantization (CVQ), a novel image tokenization paradigm that replaces patch-wise tokens with channel-wise tokens. Unlike conventional vector quantization, which assigns a discrete token to each patch feature vector, CVQ quantizes each channel of the feature map. This f

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### 4. A Multimodal 3D Foundation Model for Light Sheet Fluorescence Microscopy Enables Few-Shot Segmentation, Classification, and Deblurring

- **arXiv:** `2605.26026` | [Abstract](https://arxiv.org/abs/2605.26026v1) | [PDF](https://arxiv.org/pdf/2605.26026v1)
- **Authors:** Adina Scheinfeld, Haotan Zhang, Shang Mu, Rudolf L. M. van Herten, Lucas Stoffl et al.
- **Published:** 2026-05-25

Light sheet fluorescence microscopy (LSM) enables high-resolution, three-dimensional (3D) imaging of biological specimens, providing rich volumetric data for studying cellular organization, pathology, and vascular networks. However, the size, dimensionality, and annotation burden of LSM data make su

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### 5. MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

- **arXiv:** `2605.26006` | [Abstract](https://arxiv.org/abs/2605.26006v1) | [PDF](https://arxiv.org/pdf/2605.26006v1)
- **Authors:** Bin Li, Ruichi Zhang, Han Liang, Jingyan Zhang, Juze Zhang et al.
- **Published:** 2026-05-25

Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typically follow either a two-stage paradigm that combines kinematic motion generation with physics-based tracking, or an end-to-end imitation-learning par

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## 📊 CTR / Ranking / IR (0 papers)

_No new papers._

## 🤖 Agent / Auto Research (0 papers)

_No new papers._

_Report generated at 2026-05-26 14:00:01 CST_