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Hongbo Liu

7 accepted papers

2026

EchoGen: Cycle-Consistent Learning for Unified Layout-Image Generation and Understanding

AAAI 2026technical

In this work, we present EchoGen, a unified framework for layout-to-image generation and image grounding, capable of generating images with both accurate layout and high fidelity to the text description.(e.g., spatial relationship), and grounding the image robustly at the same time. We believe that

Cited by 0SourcePDFScholar
2026

From Subtle to Significant: Prompt-Driven Self-Improving Optimization in Test-Time Graph OOD Detection

AAAI 2026technical

Graph Out-of-Distribution (OOD) detection aims to identify whether a test graph deviates from the distribution of graphs observed during training, which is critical for ensuring the reliability of Graph Neural Networks (GNNs) when deployed in open-world scenarios. Recent advances in graph OOD detect

Cited by 0SourcePDFScholar
2026

Seeing Depth Through Frequency and Motion: A Progressive Training Paradigm for Monocular Depth Estimation

CVPR 2026

Self-supervised monocular depth estimation has achieved remarkable progress in recent years, yet frequency aliasing and the lack of fine-grained cross-frame motion modeling still lead to blurred depth boundaries and suboptimal camera motion estimation.To address these challenges, we propose a progre

Cited by 0SourcecodeScholar
2026

Towards Distance-Invariant Radio Frequency Fingerprinting via Augmented Unsupervised Learning

AAAI 2026technical

Radio Frequency Fingerprinting (RFF) exploits inherent hardware-level imperfections of wireless transmitters as unclonable identifiers for device identification. These unique signatures, concealed in transmitted signals, inevitably experience complex distortions during wireless propagation (i.e., co

Cited by 0SourcePDFScholar
2025

ShotBench: Expert-Level Cinematic Understanding in Vision-Language Models

NeurIPS 2025poster

Recent Vision-Language Models (VLMs) have shown strong performance in general-purpose visual understanding and reasoning, but their ability to comprehend the visual grammar of movie shots remains underexplored and insufficiently evaluated. To bridge this gap, we present \textbf{ShotBench}, a dedicat…

Cited by 0SourceScholar
2024

PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild

CVPR 2024poster

Video quality assessment (VQA) is a challenging problem due to the numerous factors that can affect the perceptual quality of a video e.g. content attractiveness distortion type motion pattern and level. However annotating the Mean opinion score (MOS) for videos is expensive and time-consuming which…

Cited by 5SourcePDFScholar