Yizhou Wang

MTPano: Multi-Task Panoramic Scene Understanding via Label-Free Integration of Dense Prediction Priors

Jingdong Zhang, Xiaohang Zhan, Lingzhi Zhang, Yizhou Wang et autres

Comprehensive panoramic scene understanding is critical for immersive applications, yet it remains challenging due to the scarcity of high-resolution, multi-task annotations. While perspective foundation models have achieved success through data scaling, directly adapting them to the panoramic domain often fails due to …

us (code pays fourni par la source)

Distorted or Fabricated? A Survey on Hallucination in Video LLMs

Yiyang Huang, Yitian Zhang, Yizhou Wang, Mingyuan Zhang et autres

Despite significant progress in video-language modeling, hallucinations remain a persistent challenge in Video Large Language Models (Vid-LLMs), referring to outputs that appear plausible yet contradict the content of the input video. This survey presents a comprehensive analysis of hallucinations in Vid-LLMs and …

us (code pays fourni par la source)

Distorted or Fabricated? A Survey on Hallucination in Video LLMs

Yiyang Huang, Yitian Zhang, Yizhou Wang, Mingyuan Zhang et autres

Despite significant progress in video-language modeling, hallucinations remain a persistent challenge in Video Large Language Models (Vid-LLMs), referring to outputs that appear plausible yet contradict the content of the input video.This survey presents a comprehensive analysis of hallucinations in Vid-LLMs and introduces …

us, bd (code pays fourni par la source)

FreeCloth: Free-form Generation Enhances Challenging Clothed Human Modeling

Hang Ye, Xiaoxuan Ma, Hai Ci, Yizhou Wang

Achieving realistic animated human avatars requires accurate modeling of pose-dependent clothing deformations. Existing learning-based methods heavily rely on the Linear Blend Skinning (LBS) of minimally-clothed human models like SMPL to model deformation. However, they struggle to handle loose clothing, such as long …

cn (code pays fourni par la source)

Towards Zero-shot 3D Anomaly Localization

Yizhou Wang, Kuan–Chuan Peng, Yun Fu

3D anomaly detection and localization is of great significancefor industrial inspection. Prior 3D anomaly detection and localization methods focus on the setting that the testing data share the same category as the training data which is normal. However, in real-world applications, the …

mx, us (code pays fourni par la source)

EgoAgent: A Joint Predictive Agent Model in Egocentric Worlds

Lu Chen, Yizhou Wang, Shixiang Tang, Qi Ma et autres

Learning an agent model that behaves like humans-capable of jointly perceiving the environment, predicting the future, and taking actions from a first-person perspective-is a fundamental challenge in computer vision. Existing methods typically train separate models for these abilities, which fail to capture …

A Study on Reducing Illegal Wildlife Trade Based on Data-Driven Predictive Model

Bo Han, Jiaqing Liu, Yizhou Wang, Ye Lv et autres

As an important part of the ecological environment and the main part of biodiversity, wildlife is a very important resource for the development of human civilization, and has increasingly become a hotspot and a focus of attention around the world. The aim …

cn (code pays fourni par la source)

Towards Zero-shot 3D Anomaly Localization

Yizhou Wang, Kuan–Chuan Peng, Yun Fu

3D anomaly detection and localization is of great significance for industrial inspection. Prior 3D anomaly detection and localization methods focus on the setting that the testing data share the same category as the training data which is normal. However, in real-world applications, …

DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM

Yixuan Wu, Yizhou Wang, Shixiang Tang, Wenhao Wu et autres

gb, cn, hk, au (code pays fourni par la source)

SLA2P: Self-Supervised Anomaly Detection With Adversarial Perturbation

Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu et autres

Anomaly detection is a foundational yet difficult problem in machine learning. In this work, we propose a new and effective framework, dubbed as SLA2P, for unsupervised anomaly detection. Following the extraction of delegate embeddings from raw data, we implement random projections on …

us (code pays fourni par la source)

DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM

Yixuan Wu, Yizhou Wang, Shixiang Tang, Wenhao Wu et autres

We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object detection ability of multimodal large language models (MLLMs), such as GPT-4V and Gemini. Our approach consists of a detection prompting toolkit inspired by high-precision detection priors and a new Chain-of-Thought …

An Unrolled Implicit Regularization Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging with Convergence Guarantee

Yan Yang, Yizhou Wang, Jiazhen Wang, Jian Sun et autres

Abstract. Parallel imaging (PI), relying on multicoils to sense [Formula: see text]-space data, is an effective technique to accelerate magnetic resonance imaging by exploiting spatial sensitivity coding of multiple coils, with an integrated compressive sensing (CS) technology to achieve higher acceleration. In …

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