activity
20192026
most citedUnified learning-based lossy and lossless JPEG recompression

12 citations · 36 across the 41 of their papers we have counts for

collaborators

42 papers

cs.CV2026

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…

cs.CV2026

SoLAR: Error-Resilient Streamable Long-Horizon Free-Viewpoint Video Reconstruction with Anchor Activation and Latent Recalibration

Haotian Zhang, Xu Mo, Yixin Yu +7

Free-Viewpoint Video (FVV) has emerged as a cornerstone of next-generation immersive media systems and attracted widespread attention. Previous methods primarily focus on short vid…

cs.CV2026

Training-Free Image Editing with Visual Context Integration and Concept Alignment

Rui Song, Guo-Hua Wang, Qing-Guo Chen +6

In image editing, it is essential to incorporate a context image to convey the user's precise requirements, such as subject appearance or image style. Existing training-based visua…

cs.CV2026

RAWIC: Bit-Depth Adaptive Lossless Raw Image Compression

Chunhang Zheng, Tongda Xu, Mingli Xie +2

Raw images preserve linear sensor measurements and high bit-depth information crucial for advanced vision tasks and photography applications, yet their storage remains challenging…

cs.CV2026

Parallax to Align Them All: An OmniParallax Attention Mechanism for Distributed Multi-View Image Compression

Haotian Zhang, Feiyue Long, Yixin Yu +7

Multi-view image compression (MIC) aims to achieve high compression efficiency by exploiting inter-image correlations, playing a crucial role in 3D applications. As a subfield of M…

cs.CV2026

Making Reconstruction FID Predictive of Diffusion Generation FID

Tongda Xu, Mingwei He, Shady Abu-Hussein +6

It is well known that the reconstruction FID (rFID) of a VAE is poorly correlated with the generation FID (gFID) of a latent diffusion model. We propose interpolated FID (iFID), a…

cs.CV2025

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…

cs.CV2025

Benchmarking and Enhancing VLM for Compressed Image Understanding

Zifu Zhang, Tongda Xu, Siqi Li +4

With the rapid development of Vision-Language Models (VLMs) and the growing demand for their applications, efficient compression of the image inputs has become increasingly importa…

cs.LG2025

Training-Free Vector Quantization via Gaussian VAEs

Tongda Xu, Wendi Zheng, Jiajun He +4

Vector-quantized variational autoencoders (VQ-VAEs) are discrete autoencoders that compress images into discrete tokens. However, they are difficult to train due to discretization.…

cs.CV2025

V-Shuffle: Zero-Shot Style Transfer via Value Shuffle

Haojun Tang, Qiwei Lin, Tongda Xu +2

Attention injection-based style transfer has achieved remarkable progress in recent years. However, existing methods often suffer from content leakage, where the undesired semantic…

cs.CV2025

Versatile Recompression-Aware Perceptual Image Super-Resolution

Mingwei He, Tongda Xu, Xingtong Ge +3

Perceptual image super-resolution (SR) methods restore degraded images and produce sharp outputs. In practice, those outputs are usually recompressed for storage and transmission.…

eess.IV2025

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…

cs.CV2025

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…

cs.CV2025

PICD: Versatile Perceptual Image Compression with Diffusion Rendering

Tongda Xu, Jiahao Li, Bin Li +3

Recently, perceptual image compression has achieved significant advancements, delivering high visual quality at low bitrates for natural images. However, for screen content, existi…

cs.CV2025

CoopDETR: A Unified Cooperative Perception Framework for 3D Detection via Object Query

Zhe Wang, Shaocong Xu, Xucai Zhuang +5

Cooperative perception enhances the individual perception capabilities of autonomous vehicles (AVs) by providing a comprehensive view of the environment. However, balancing percept…

cs.CV2025

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…

cs.CV2024

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…

eess.IV2024

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…

eess.IV2024★ 2 cited

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…

cs.CV2024

Noise Dimension of GAN: An Image Compression Perspective

Ziran Zhu, Tongda Xu, Ling Li +1

Generative adversial network (GAN) is a type of generative model that maps a high-dimensional noise to samples in target distribution. However, the dimension of noise required in G…

cs.CV2024

Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers

Tongda Xu, Ziran Zhu, Jian Li +8

Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution , with a predefined diffusion model , an operator , and a m…

eess.IV2024

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…

eess.IV2024

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,…

cs.CV2024

EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection

Zhe Wang, Siqi Fan, Xiaoliang Huo +5

In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of…