14 citations · 36 across the 14 of their papers we have counts for
17 papers
ThinkV2V: Unleashing the Reasoning Capability of MLLMs for Instruction-Guided Video Editing
Donghao Zhou, Haoyang He, Fan Zhang +10
Instruction-guided video editing has made significant progress, yet existing methods use multimodal large language models (MLLMs) primarily as semantic encoders, so they often fall…
MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection
Xiaobin Hu, Haoyang He, Bo Yin +5
While recent advancements in anomaly detection have demonstrated the efficacy of CNN- and Transformer-based approaches, these architectures face inherent limitations: CNNs struggle…
Multi-Dimensional Knowledge Profiling with Large-Scale Literature Database and Hierarchical Retrieval
Zhucun Xue, Jiangning Zhang, Juntao Jiang +6
The rapid expansion of research across machine learning, vision, and language has produced a volume of publications that is increasingly difficult to synthesize. Traditional biblio…
JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editing
Xiaohu Huang, Haoyang He, Hao Zhou +3
In this paper, we present JoVA, a streamlined framework that unifies joint video-audio generation and editing. While existing methods often rely on fragmented, task-specific archit…
OpenVE-3M: A Large-Scale High-Quality Dataset for Instruction-Guided Video Editing
Haoyang He, Jie Wang, Jiangning Zhang +5
The quality and diversity of instruction-based image editing datasets are continuously increasing, yet large-scale, high-quality datasets for instruction-based video editing remain…
EfficientIML: Efficient High-Resolution Image Manipulation Localization
Jinhan Li, Haoyang He, Lei Xie +1
With imaging devices delivering ever-higher resolutions and the emerging diffusion-based forgery methods, current detectors trained only on traditional datasets (with splicing, cop…
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Shilong Li, Xingyuan Bu, Wenjie Wang +22
AI agents with advanced reasoning and tool-use capabilities have demonstrated impressive performance in web browsing for deep search. However, existing benchmarks such as BrowseCom…
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…
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…
MobileMamba: Lightweight Multi-Receptive Visual Mamba Network
Haoyang He, Jiangning Zhang, Yuxuan Cai +7
Previous research on lightweight models has primarily focused on CNNs and Transformer-based designs. CNNs, with their local receptive fields, struggle to capture long-range depende…
LLaVA-KD: A Framework of Distilling Multimodal Large Language Models
Yuxuan Cai, Jiangning Zhang, Haoyang He +7
The success of Large Language Models (LLMs) has inspired the development of Multimodal Large Language Models (MLLMs) for unified understanding of vision and language. However, the…
Learning Multi-view Anomaly Detection with Efficient Adaptive Selection
Haoyang He, Jiangning Zhang, Guanzhong Tian +2
This study explores the recently proposed and challenging multi-view Anomaly Detection (AD) task. Single-view tasks will encounter blind spots from other perspectives, resulting in…
A Comprehensive Library for Benchmarking Multi-class Visual Anomaly Detection
Jiangning Zhang, Haoyang He, Zhenye Gan +7
Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as indust…
PointRWKV: Efficient RWKV-Like Model for Hierarchical Point Cloud Learning
Qingdong He, Jiangning Zhang, Jinlong Peng +4
Transformers have revolutionized the point cloud learning task, but the quadratic complexity hinders its extension to long sequence and makes a burden on limited computational reso…
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Haoyang He, Yuhu Bai, Jiangning Zhang +7
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers ar…
DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection
Haoyang He, Jiangning Zhang, Hongxu Chen +6
Reconstruction-based approaches have achieved remarkable outcomes in anomaly detection. The exceptional image reconstruction capabilities of recently popular diffusion models have…
CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection
Xuhai Chen, Jiangning Zhang, Guanzhong Tian +5
This paper considers zero-shot Anomaly Detection (AD), performing AD without reference images of the test objects. We propose a framework called CLIP-AD to leverage the zero-shot c…