3 citations · 4 across the 10 of their papers we have counts for
6 papers · 1 filter
CausalCLIP: Causally-Informed Feature Disentanglement and Filtering for Generalizable Detection of Generated Images
Bo Liu, Qiao Qin, Qinghui He
The rapid advancement of generative models has increased the demand for generated image detectors capable of generalizing across diverse and evolving generation techniques. However…
CoDefend: Cross-Modal Collaborative Defense via Diffusion Purification and Prompt Optimization
Fengling Zhu, Boshi Liu, Jingyu Hua +1
Multimodal Large Language Models (MLLMs) have achieved remarkable success in tasks such as image captioning, visual question answering, and cross-modal reasoning by integrating vis…
Follow-Your-Instruction: A Comprehensive MLLM Agent for World Data Synthesis
Kunyu Feng, Yue Ma, Xinhua Zhang +9
With the growing demands of AI-generated content (AIGC), the need for high-quality, diverse, and scalable data has become increasingly crucial. However, collecting large-scale real…
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid Motions
Di Chang, Mingdeng Cao, Yichun Shi +7
Editing images with instructions to reflect non-rigid motions, camera viewpoint shifts, object deformations, human articulations, and complex interactions, poses a challenging yet…
DAPE: Dual-Stage Parameter-Efficient Fine-Tuning for Consistent Video Editing with Diffusion Models
Junhao Xia, Chaoyang Zhang, Yecheng Zhang +4
Video generation based on diffusion models presents a challenging multimodal task, with video editing emerging as a pivotal direction in this field. Recent video editing approaches…
SGC-VQGAN: Towards Complex Scene Representation via Semantic Guided Clustering Codebook
Chenjing Ding, Chiyu Wang, Boshi Liu +3
Vector quantization (VQ) is a method for deterministically learning features through discrete codebook representations. Recent works have utilized visual tokenizers to discretize v…