207 citations · 226 across the 14 of their papers we have counts for
14 papers · 1 filter
Cycle-World: Mitigating Error Accumulation in Long-term Video World Models via Reverse-Prediction Cycle Consistency
Zihan Su, Teng Hu, Jiangning Zhang +4
Autoregressive diffusion models have enabled high-quality video generation, yet their sequential nature inherently suffers from error accumulation. In long-horizon video synthesis,…
MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data
Teng Hu, Mingchun Lu, Yating Wang +6
Video world models are a foundational generative technology for embodied AI and the Metaverse, yet existing approaches are inherently limited to a single agent observing from a sin…
Evolution of Video Generative Foundations
Teng Hu, Jiangning Zhang, Hongrui Huang +7
The rapid advancement of Artificial Intelligence Generated Content (AIGC) has revolutionized video generation, enabling systems ranging from proprietary pioneers like OpenAI's Sora…
One Flight Over the Gap: A Survey from Perspective to Panoramic Vision
Xin Lin, Xian Ge, Dizhe Zhang +8
Driven by the demand for spatial intelligence and holistic scene perception, omnidirectional images (ODIs), which provide a complete 360\textdegree{} field of view, are receiving g…
UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
Zhucun Xue, Jiangning Zhang, Teng Hu +8
The quality of the video dataset (image quality, resolution, and fine-grained caption) greatly influences the performance of the video generation model. The growing demand for vide…
AdaVideoRAG: Omni-Contextual Adaptive Retrieval-Augmented Efficient Long Video Understanding
Zhucun Xue, Jiangning Zhang, Xurong Xie +4
Multimodal Large Language Models (MLLMs) perform well in video understanding but degrade on long videos due to fixed-length context and weak long-term dependency modeling. Retrieva…
So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection
Zhenglin Huang, Xiangtai Li, Xi Yang +6
Recent advances in AI-powered generative models have enabled the creation of increasingly realistic synthetic images, posing significant risks to information integrity and public t…
Generative Classifier for Domain Generalization
Shaocong Long, Qianyu Zhou, Xiangtai Li +7
Domain generalization (DG) aims to improve the generalizability of computer vision models toward distribution shifts. The mainstream DG methods predominantly focus on learning doma…
EMOv2: Pushing 5M Vision Model Frontier
Jiangning Zhang, Teng Hu, Haoyang He +6
This work focuses on developing parameter-efficient and lightweight models for dense predictions while trading off parameters, FLOPs, and performance. Our goal is to set up the new…
Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark
Jiangning Zhang, Chengjie Wang, Xiangtai Li +5
Anomaly detection (AD) is often focused on detecting anomaly areas for industrial quality inspection and medical lesion examination. However, due to the specific scenario targets,…
Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection
Jiangning Zhang, Xuhai Chen, Yabiao Wang +5
This work studies a challenging and practical issue known as multi-class unsupervised anomaly detection (MUAD). This problem requires only normal images for training while simultan…
RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model
Fengxiang Bie, Yibo Yang, Zhongzhu Zhou +10
Text-to-image generation (TTI) refers to the usage of models that could process text input and generate high fidelity images based on text descriptions. Text-to-image generation us…
TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformers
Qianyu Zhou, Xiangtai Li, Lu He +5
Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance…
Improving Video Instance Segmentation via Temporal Pyramid Routing
Xiangtai Li, Hao He, Yibo Yang +5
Video Instance Segmentation (VIS) is a new and inherently multi-task problem, which aims to detect, segment, and track each instance in a video sequence. Existing approaches are ma…