2 citations · 2 across the 15 of their papers we have counts for
16 papers
Pixel-Space Diffusion via Observation Operators
Shaojie Guo, Lichen Ma, Haoyang Tong +8
Pixel-space diffusion models directly model image distributions but remain difficult to optimize. Recent methods alleviate this challenge through target reparameterization, while s…
Dual-Prior Guided Null-Space Learning with Mixture-of-Splines for Arbitrary Medical Slice Super-Resolution
Haofei Song, Siyuan Xu, Xintian Mao +3
Arbitrary slice super-resolution reconstructs isotropic volumes from anisotropic clinical acquisitions by synthesizing intermediate slices at arbitrary scales. However, treating th…
MambaRaw: Selective State Space Modeling for Efficient 4K Raw Image Reconstruction
Peize Li, Fanhu Zeng, Tongda Xu +5
In-camera JPEG previews are ubiquitous in raw image formats and provide an sRGB reference at negligible storage cost. Although existing metadata-based reconstruction frameworks can…
MeMix: Writing Less, Remembering More for Streaming 3D Reconstruction
Jiacheng Dong, Huan Li, Sicheng Zhou +3
Reconstruction is a fundamental task in 3D vision and a fundamental capability for spatial intelligence. Particularly, streaming 3D reconstruction is central to real-time spatial p…
OARS: Process-Aware Online Alignment for Generative Real-World Image Super-Resolution
Shijie Zhao, Xuanyu Zhang, Bin Chen +8
Aligning generative real-world image super-resolution models with human visual preference is challenging due to the perception--fidelity trade-off and diverse, unknown degradations…
GaussianImage++: Boosted Image Representation and Compression with 2D Gaussian Splatting
Tiantian Li, Xinjie Zhang, Xingtong Ge +4
Implicit neural representations (INRs) have achieved remarkable success in image representation and compression, but they require substantial training time and memory. Meanwhile, r…
Never compromise with vulnerabilities: a comprehensive survey on AI governance
Yuchu Jiang, Jian Zhao, Yuchen Yuan +62
The rapid advancement of AI has expanded its capabilities across domains, yet introduced critical technical vulnerabilities, such as algorithmic bias and adversarial sensitivity, t…
Fast Training-free Perceptual Image Compression
Ziran Zhu, Tongda Xu, Minye Huang +5
Training-free perceptual image codec adopt pre-trained unconditional generative model during decoding to avoid training new conditional generative model. However, they heavily rely…
SenseFlow: Scaling Distribution Matching for Flow-based Text-to-Image Distillation
Xingtong Ge, Xin Zhang, Tongda Xu +4
The Distribution Matching Distillation (DMD) has been successfully applied to text-to-image diffusion models such as Stable Diffusion (SD) 1.5. However, vanilla DMD suffers from co…
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Tongda Xu, Xiyan Cai, Xinjie Zhang +7
Recent advancements in diffusion models have been leveraged to address inverse problems without additional training, and Diffusion Posterior Sampling (DPS) (Chung et al., 2022a) is…
MEGA: Memory-Efficient 4D Gaussian Splatting for Dynamic Scenes
Xinjie Zhang, Zhening Liu, Yifan Zhang +7
4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and…
Task-Aware Encoder Control for Deep Video Compression
Xingtong Ge, Jixiang Luo, Xinjie Zhang +7
Prior research on deep video compression (DVC) for machine tasks typically necessitates training a unique codec for each specific task, mandating a dedicated decoder per task. In c…
Boosting Neural Representations for Videos with a Conditional Decoder
Xinjie Zhang, Ren Yang, Dailan He +5
Implicit neural representations (INRs) have emerged as a promising approach for video storage and processing, showing remarkable versatility across various video tasks. However, ex…
Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive Quantization
Jixiang Luo, Yan Wang, Hongwei Qin
Learned Image Compression (LIC) has achieved dramatic progress regarding objective and subjective metrics. MSE-based models aim to improve objective metrics while generative models…
GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting
Xinjie Zhang, Xingtong Ge, Tongda Xu +6
Implicit neural representations (INRs) recently achieved great success in image representation and compression, offering high visual quality and fast rendering speeds with 10-1000…
CAMSIC: Content-aware Masked Image Modeling Transformer for Stereo Image Compression
Xinjie Zhang, Shenyuan Gao, Zhening Liu +6
Existing learning-based stereo image codec adopt sophisticated transformation with simple entropy models derived from single image codecs to encode latent representations. However,…