305 citations · 822 across the 79 of their papers we have counts for
18 papers · 1 filter
StealthDiffusion: Towards Evading Diffusion Forensic Detection through Diffusion Model
Ziyin Zhou, Ke Sun, Zhongxi Chen +3
The rapid progress in generative models has given rise to the critical task of AI-Generated Content Stealth (AIGC-S), which aims to create AI-generated images that can evade both f…
3D-GRES: Generalized 3D Referring Expression Segmentation
Changli Wu, Yihang Liu, Jiayi Ji +6
3D Referring Expression Segmentation (3D-RES) is dedicated to segmenting a specific instance within a 3D space based on a natural language description. However, current approaches…
INF-LLaVA: Dual-perspective Perception for High-Resolution Multimodal Large Language Model
Yiwei Ma, Zhibin Wang, Xiaoshuai Sun +4
With advancements in data availability and computing resources, Multimodal Large Language Models (MLLMs) have showcased capabilities across various fields. However, the quadratic c…
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models
Mingrui Wu, Jiayi Ji, Oucheng Huang +4
The issue of hallucinations is a prevalent concern in existing Large Vision-Language Models (LVLMs). Previous efforts have primarily focused on investigating object hallucinations,…
Multi-branch Collaborative Learning Network for 3D Visual Grounding
Zhipeng Qian, Yiwei Ma, Zhekai Lin +4
3D referring expression comprehension (3DREC) and segmentation (3DRES) have overlapping objectives, indicating their potential for collaboration. However, existing collaborative ap…
Exploring Phrase-Level Grounding with Text-to-Image Diffusion Model
Danni Yang, Ruohan Dong, Jiayi Ji +4
Recently, diffusion models have increasingly demonstrated their capabilities in vision understanding. By leveraging prompt-based learning to construct sentences, these models have…
ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models
Mingrui Wu, Xinyue Cai, Jiayi Ji +7
In this work, we propose a training-free method to inject visual prompts into Multimodal Large Language Models (MLLMs) through test-time optimization of a learnable latent variable…
Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models
Qiong Wu, Zhaoxi Ke, Yiyi Zhou +2
Recently, mixture of experts (MoE) has become a popular paradigm for achieving the trade-off between modal capacity and efficiency of multi-modal large language models (MLLMs). Dif…
AnyTrans: Translate AnyText in the Image with Large Scale Models
Zhipeng Qian, Pei Zhang, Baosong Yang +5
This paper introduces AnyTrans, an all-encompassing framework for the task-Translate AnyText in the Image (TATI), which includes multilingual text translation and text fusion withi…
Beat: Bi-directional One-to-Many Embedding Alignment for Text-based Person Retrieval
Yiwei Ma, Xiaoshuai Sun, Jiayi Ji +3
Text-based person retrieval (TPR) is a challenging task that involves retrieving a specific individual based on a textual description. Despite considerable efforts to bridge the ga…
SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation
Danni Yang, Jiayi Ji, Yiwei Ma +4
In this paper, we introduce SemiRES, a semi-supervised framework that effectively leverages a combination of labeled and unlabeled data to perform RES. A significant hurdle in appl…
Image Captioning via Dynamic Path Customization
Yiwei Ma, Jiayi Ji, Xiaoshuai Sun +4
This paper explores a novel dynamic network for vision and language tasks, where the inferring structure is customized on the fly for different inputs. Most previous state-of-the-a…
Deep Instruction Tuning for Segment Anything Model
Xiaorui Huang, Gen Luo, Chaoyang Zhu +4
Recently, Segment Anything Model (SAM) has become a research hotspot in the fields of multimedia and computer vision, which exhibits powerful yet versatile capabilities on various…
DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery Analysis
Zhongxi Chen, Ke Sun, Ziyin Zhou +4
The rapid progress in deep learning has given rise to hyper-realistic facial forgery methods, leading to concerns related to misinformation and security risks. Existing face forger…
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
Gen Luo, Yiyi Zhou, Yuxin Zhang +3
Despite remarkable progress, existing multimodal large language models (MLLMs) are still inferior in granular visual recognition. Contrary to previous works, we study this problem…
Not All Attention is Needed: Parameter and Computation Efficient Transfer Learning for Multi-modal Large Language Models
Qiong Wu, Weihao Ye, Yiyi Zhou +2
In this paper, we propose a novel parameter and computation efficient tuning method for Multi-modal Large Language Models (MLLMs), termed Efficient Attention Skipping (EAS). Concre…
Fast Text-to-3D-Aware Face Generation and Manipulation via Direct Cross-modal Mapping and Geometric Regularization
Jinlu Zhang, Yiyi Zhou, Qiancheng Zheng +5
Text-to-3D-aware face (T3D Face) generation and manipulation is an emerging research hot spot in machine learning, which still suffers from low efficiency and poor quality. In this…
Towards Efficient Diffusion-Based Image Editing with Instant Attention Masks
Siyu Zou, Jiji Tang, Yiyi Zhou +5
Diffusion-based Image Editing (DIE) is an emerging research hot-spot, which often applies a semantic mask to control the target area for diffusion-based editing. However, most exis…