3 citations · 3 across the 12 of their papers we have counts for
13 papers
KwaiMind Technical Report
Junlong Wu, Zijun Li, Yuting Hu +14
Commercial image editing requires product identity preservation, accurate text rendering, and user appeal alongside general editing quality. We present KwaiMind, an image editing s…
FlowErase-OPD: Multi-Concept Erasure via Anchored On-Policy Distillation in Flow Matching Models
Yi Sun, Yimin Zhou, Xinhao Zhong +3
Recent advances in flow matching models have substantially improved the quality of text-to-image generation, but have also raised increasing safety concerns due to their potential…
DetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation
Zijun Li, Yimin Zhou, Jia Sun +12
Diffusion-based generative AI has achieved remarkable success in e-commerce applications such as virtual try-on, poster generation, and product background synthesis. However, when…
FlowErase-RL: Rethinking Concept Erasure as Reward Optimization in Flow Matching Models
Yi Sun, Zhiqi Zhang, Xinhao Zhong +5
Recent advances in flow matching models have significantly improved text-to-image generation quality, but also introduce growing safety risks due to the generation of harmful or un…
Towards Efficient Low-rate Image Compression with Frequency-aware Diffusion Prior Refinement
Yichong Xia, Yimin Zhou, Jinpeng Wang +1
Recent advancements in diffusion-based generative priors have enabled visually plausible image compression at extremely low bit rates. However, existing approaches suffer from slow…
ActErase: A Training-Free Paradigm for Precise Concept Erasure via Activation Redirection
Yi Sun, Xinhao Zhong, Hongyan Li +4
Recent advances in text-to-image diffusion models have demonstrated remarkable generation capabilities, yet they raise significant concerns regarding safety, copyright, and ethical…
Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression
Xiang Liu, Yimin Zhou, Jinxiang Wang +9
The recent advent of 3D Gaussian Splatting (3DGS) has marked a significant breakthrough in real-time novel view synthesis. However, the rapid proliferation of 3DGS-based algorithms…
Closing the Safety Gap: Surgical Concept Erasure in Visual Autoregressive Models
Xinhao Zhong, Yimin Zhou, Zhiqi Zhang +6
The rapid progress of visual autoregressive (VAR) models has brought new opportunities for text-to-image generation, but also heightened safety concerns. Existing concept erasure t…
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets
Xulin Gu, Xinhao Zhong, Zhixing Wei +5
Dataset distillation (DD) has emerged as a powerful paradigm for dataset compression, enabling the synthesis of compact surrogate datasets that approximate the training utility of…
High Quality Underwater Image Compression with Adaptive Color Correction
Yimin Zhou, Yichong Xia, Sicheng Pan +6
With the increasing exploration and exploitation of the underwater world, underwater images have become a critical medium for human interaction with marine environments, driving ex…
FaSDiff: Balancing Perception and Semantics in Face Compression via Stable Diffusion Priors
Yimin Zhou, Yichong Xia, Bin Chen +4
With the increasing deployment of facial image data across a wide range of applications, efficient compression tailored to facial semantics has become critical for both storage and…
MambaVC: Learned Visual Compression with Selective State Spaces
Shiyu Qin, Jinpeng Wang, Yimin Zhou +6
Learned visual compression is an important and active task in multimedia. Existing approaches have explored various CNN- and Transformer-based designs to model content distribution…
Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression
Shiyu Qin, Yimin Zhou, Jinpeng Wang +4
In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression. Our approach covers a wide range of compression rates with the assi…