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Tiange Xiang

9 accepted papers

2026

QUANTIPHY: A Quantitative Benchmark Evaluating Physical Reasoning Abilities of Vision-Language Models

CVPR 2026

Understanding the physical world is essential for generalist AI agents. However, it remains unclear whether state-of-the-art vision perception models (e.g., large VLMs) can perform quantitative physical reasoning tasks. Existing evaluations are predominantly VQA-based and qualitative, offering limit

Cited by 0SourcecodeScholar
2026

ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body

CVPR 2026

Human communication is inherently multimodal and social: words, prosody, and body language jointly carry intent. Yet most prior systems model human behavior as a translation task--co-speech gesture or text-to-motion that maps a fixed utterance to motion clips--without requiring agentic decision-maki

Cited by 0SourceScholar
2025

Repurposing 2D Diffusion Models with Gaussian Atlas for 3D Generation

ICCV 2025poster

Text-to-image diffusion models have seen significant development recently due to increasing availability of paired 2D data. Although a similar trend is emerging in 3D generation, the limited availability of high-quality 3D data has resulted in less competitive 3D diffusion models compared to their 2…

Cited by 0SourcePDFScholar
2024

OccFusion: Rendering Occluded Humans with Generative Diffusion Priors

NeurIPS 2024poster

Existing human rendering methods require every part of the human to be fully visible throughout the input video. However, this assumption does not hold in real-life settings where obstructions are common, resulting in only partial visibility of the human. Considering this, we present OccFusion, an a…

Cited by 3SourcePDFScholar
2023

DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models

ICLR 2023poster

Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique. However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting in increased costs and patient discomfort, and decreased throughput. Thus, there is great interest in denoising MRI scan…

2023

SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection

CVPR 2023poster

Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. To exploit this structured information, we propose the use of Space-aware Memory Queues for In-painting and Detecting anomalies…

2023

Seeing Beyond the Brain: Conditional Diffusion Model With Sparse Masked Modeling for Vision Decoding

CVPR 2023poster

Decoding visual stimuli from brain recordings aims to deepen our understanding of the human visual system and build a solid foundation for bridging human and computer vision through the Brain-Computer Interface. However, reconstructing high-quality images with correct semantics from brain recordings…

2021

Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis

ICCV 2021poster

Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper, we present a novel method for aggregating hypothetical curves in point clouds. Sequences of connected points (curves) are initially grouped by taking guided walks in the point clouds, and then subsequentl…

Cited by 367PDFcodeScholar