34 citations · 46 across the 16 of their papers we have counts for
15 papers · 1 filter
CSD: Content-aware Speculative Decoding for Efficient Image Generation
Mingcheng Wang, Junbo Qiao, Yunchen Li +8
Speculative decoding (SD) has emerged as a key solution to accelerate the inference of autoregressive models. However, in the field of image generation, it faces the challenge of l…
RealSR-R1: Reinforcement Learning for Real-World Image Super-Resolution with Vision-Language Chain-of-Thought
Junbo Qiao, Miaomiao Cai, Wei Li +5
Real-World Image Super-Resolution is one of the most challenging task in image restoration. However, existing methods struggle with an accurate understanding of degraded image cont…
DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution
Miaomiao Cai, Simiao Li, Wei Li +4
Recent advances in diffusion models have improved Real-World Image Super-Resolution (Real-ISR), but existing methods lack human feedback integration, risking misalignment with huma…
Autoregressive Image Generation with Vision Full-view Prompt
Miaomiao Cai, Guanjie Wang, Wei Li +4
In autoregressive (AR) image generation, models based on the 'next-token prediction' paradigm of LLMs have shown comparable performance to diffusion models by reducing inductive bi…
Dynamic Contrastive Knowledge Distillation for Efficient Image Restoration
Yunshuai Zhou, Junbo Qiao, Jincheng Liao +6
Knowledge distillation (KD) is a valuable yet challenging approach that enhances a compact student network by learning from a high-performance but cumbersome teacher model. However…
GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization
Yirui Chen, Xudong Huang, Quan Zhang +9
The extraordinary ability of generative models emerges as a new trend in image editing and generating realistic images, posing a serious threat to the trustworthiness of multimedia…
Collaboration of Teachers for Semi-supervised Object Detection
Liyu Chen, Huaao Tang, Yi Wen +4
Recent semi-supervised object detection (SSOD) has achieved remarkable progress by leveraging unlabeled data for training. Mainstream SSOD methods rely on Consistency Regularizatio…
LIPT: Latency-aware Image Processing Transformer
Junbo Qiao, Wei Li, Haizhen Xie +5
Transformer is leading a trend in the field of image processing. Despite the great success that existing lightweight image processing transformers have achieved, they are tailored…
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li +5
Knowledge distillation (KD) is a promising yet challenging model compression technique that transfers rich learning representations from a well-performing but cumbersome teacher mo…
Distilling Semantic Priors from SAM to Efficient Image Restoration Models
Quan Zhang, Xiaoyu Liu, Wei Li +6
In image restoration (IR), leveraging semantic priors from segmentation models has been a common approach to improve performance. The recent segment anything model (SAM) has emerge…
IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions
Zhijun Tu, Kunpeng Du, Hanting Chen +4
Recent advances have demonstrated the powerful capability of transformer architecture in image restoration. However, our analysis indicates that existing transformerbased methods c…
GenDet: Towards Good Generalizations for AI-Generated Image Detection
Mingjian Zhu, Hanting Chen, Mouxiao Huang +4
The misuse of AI imagery can have harmful societal effects, prompting the creation of detectors to combat issues like the spread of fake news. Existing methods can effectively dete…
IFT: Image Fusion Transformer for Ghost-free High Dynamic Range Imaging
Hailing Wang, Wei Li, Yuanyuan Xi +4
Multi-frame high dynamic range (HDR) imaging aims to reconstruct ghost-free images with photo-realistic details from content-complementary but spatially misaligned low dynamic rang…
Data Upcycling Knowledge Distillation for Image Super-Resolution
Yun Zhang, Wei Li, Simiao Li +6
Knowledge distillation (KD) compresses deep neural networks by transferring task-related knowledge from cumbersome pre-trained teacher models to compact student models. However, cu…
GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image
Mingjian Zhu, Hanting Chen, Qiangyu Yan +7
The extraordinary ability of generative models to generate photographic images has intensified concerns about the spread of disinformation, thereby leading to the demand for detect…