activity
20122024
most citedM2-CLIP: A Multimodal, Multi-task Adapting Framework for Video Action Recognition

4 citations · 9 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2024

Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for Image Editing

Haonan Lin, Mengmeng Wang, Jiahao Wang +7

Text-guided diffusion models have significantly advanced image editing, enabling high-quality and diverse modifications driven by text prompts. However, effective editing requires…

cs.CV2024

Disentangled Noisy Correspondence Learning

Zhuohang Dang, Minnan Luo, Jihong Wang +6

Cross-modal retrieval is crucial in understanding latent correspondences across modalities. However, existing methods implicitly assume well-matched training data, which is impract…

cs.CV20241 cited

Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models

Wenbin An, Feng Tian, Jiahao Nie +7

Knowledge-based Visual Question Answering (KVQA) requires both image and world knowledge to answer questions. Current methods first retrieve knowledge from the image and external k…

cs.CV2024

Timestep-Aware Correction for Quantized Diffusion Models

Yuzhe Yao, Feng Tian, Jun Chen +4

Diffusion models have marked a significant breakthrough in the synthesis of semantically coherent images. However, their extensive noise estimation networks and the iterative gener…

cs.CV2024

TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On

Jiazheng Xing, Chao Xu, Yijie Qian +5

Virtual try-on focuses on adjusting the given clothes to fit a specific person seamlessly while avoiding any distortion of the patterns and textures of the garment. However, the cl…

cs.CV2024

DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation

Haonan Lin, Mengmeng Wang, Yan Chen +6

While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centered images, novel challenges arise with a nuanced task of "identity fine editi…