activity
20182026
most citedBlind Image Super-Resolution via Contrastive Representation Learning

34 citations · 299 across the 48 of their papers we have counts for

collaborators

49 papers

cs.CV2026

BudSplat: Feed-forward 3D Gaussian Splatting under a Rendering Budget

Muyu Xu, Fangneng Zhan, Yu Wei +2

Feed-forward 3D Gaussian Splatting has recently emerged as a promising alternative to per-scene optimization, enabling fast novel view synthesis by predicting Gaussian primitives d…

cs.CV2026

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

Keming Wu, Zuhao Yang, Kaichen Zhang +24

Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning…

cs.CV2025

MuSASplat: Efficient Sparse-View 3D Gaussian Splats via Lightweight Multi-Scale Adaptation

Muyu Xu, Fangneng Zhan, Xiaoqin Zhang +2

Sparse-view 3D Gaussian splatting seeks to render high-quality novel views of 3D scenes from a limited set of input images. While recent pose-free feed-forward methods leveraging p…

cs.CV2025

SOGS: Second-Order Anchor for Advanced 3D Gaussian Splatting

Jiahui Zhang, Fangneng Zhan, Ling Shao +1

Anchor-based 3D Gaussian splatting (3D-GS) exploits anchor features in 3D Gaussian prediction, which has achieved impressive 3D rendering quality with reduced Gaussian redundancy.…

cs.CV2024★ 1 cited

MixLight: Borrowing the Best of both Spherical Harmonics and Gaussian Models

Xinlong Ji, Fangneng Zhan, Shijian Lu +2

Accurately estimating scene lighting is critical for applications such as mixed reality. Existing works estimate illumination by generating illumination maps or regressing illumina…

cs.CV2024★ 2 cited

FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization

Jiahui Zhang, Fangneng Zhan, Muyu Xu +2

3D Gaussian splatting has achieved very impressive performance in real-time novel view synthesis. However, it often suffers from over-reconstruction during Gaussian densification w…

cs.CV2024

StyleGaussian: Instant 3D Style Transfer with Gaussian Splatting

Kunhao Liu, Fangneng Zhan, Muyu Xu +3

We introduce StyleGaussian, a novel 3D style transfer technique that allows instant transfer of any image's style to a 3D scene at 10 frames per second (fps). Leveraging 3D Gaussia…

cs.CV2023★ 5 cited

AI-Generated Images as Data Source: The Dawn of Synthetic Era

Zuhao Yang, Fangneng Zhan, Kunhao Liu +2

The advancement of visual intelligence is intrinsically tethered to the availability of large-scale data. In parallel, generative Artificial Intelligence (AI) has unlocked the pote…

cs.CV2023

Pose-Free Neural Radiance Fields via Implicit Pose Regularization

Jiahui Zhang, Fangneng Zhan, Yingchen Yu +5

Pose-free neural radiance fields (NeRF) aim to train NeRF with unposed multi-view images and it has achieved very impressive success in recent years. Most existing works share the…

cs.CV2023

WaveNeRF: Wavelet-based Generalizable Neural Radiance Fields

Muyu Xu, Fangneng Zhan, Jiahui Zhang +5

Neural Radiance Field (NeRF) has shown impressive performance in novel view synthesis via implicit scene representation. However, it usually suffers from poor scalability as requir…

cs.CV2023★ 8 cited

Weakly Supervised 3D Open-vocabulary Segmentation

Kunhao Liu, Fangneng Zhan, Jiahui Zhang +6

Open-vocabulary segmentation of 3D scenes is a fundamental function of human perception and thus a crucial objective in computer vision research. However, this task is heavily impe…

cs.CV2023★ 1 cited

General Neural Gauge Fields

Fangneng Zhan, Lingjie Liu, Adam Kortylewski +1

The recent advance of neural fields, such as neural radiance fields, has significantly pushed the boundary of scene representation learning. Aiming to boost the computation efficie…

cs.CV2023

Audio-Driven Talking Face Generation with Diverse yet Realistic Facial Animations

Rongliang Wu, Yingchen Yu, Fangneng Zhan +3

Audio-driven talking face generation, which aims to synthesize talking faces with realistic facial animations (including accurate lip movements, vivid facial expression details and…

cs.CV2023

POCE: Pose-Controllable Expression Editing

Rongliang Wu, Yingchen Yu, Fangneng Zhan +3

Facial expression editing has attracted increasing attention with the advance of deep neural networks in recent years. However, most existing methods suffer from compromised editin…

cs.CV2023

Face Transformer: Towards High Fidelity and Accurate Face Swapping

Kaiwen Cui, Rongliang Wu, Fangneng Zhan +1

Face swapping aims to generate swapped images that fuse the identity of source faces and the attributes of target faces. Most existing works address this challenging task through 3…

cs.CV2023★ 1 cited

KD-DLGAN: Data Limited Image Generation via Knowledge Distillation

Kaiwen Cui, Yingchen Yu, Fangneng Zhan +3

Generative Adversarial Networks (GANs) rely heavily on large-scale training data for training high-quality image generation models. With limited training data, the GAN discriminato…

cs.CV2023★ 3 cited

StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields

Kunhao Liu, Fangneng Zhan, Yiwen Chen +5

3D style transfer aims to render stylized novel views of a 3D scene with multi-view consistency. However, most existing work suffers from a three-way dilemma over accurate geometry…

cs.CV2023

Regularized Vector Quantization for Tokenized Image Synthesis

Jiahui Zhang, Fangneng Zhan, Christian Theobalt +1

Quantizing images into discrete representations has been a fundamental problem in unified generative modeling. Predominant approaches learn the discrete representation either in a…

cs.CV2022★ 3 cited

Latent Multi-Relation Reasoning for GAN-Prior based Image Super-Resolution

Jiahui Zhang, Fangneng Zhan, Yingchen Yu +3

Recently, single image super-resolution (SR) under large scaling factors has witnessed impressive progress by introducing pre-trained generative adversarial networks (GANs) as prio…

cs.CV2022

Auto-regressive Image Synthesis with Integrated Quantization

Fangneng Zhan, Yingchen Yu, Rongliang Wu +4

Deep generative models have achieved conspicuous progress in realistic image synthesis with multifarious conditional inputs, while generating diverse yet high-fidelity images remai…

cs.CV2022

Towards Counterfactual Image Manipulation via CLIP

Yingchen Yu, Fangneng Zhan, Rongliang Wu +6

Leveraging StyleGAN's expressivity and its disentangled latent codes, existing methods can achieve realistic editing of different visual attributes such as age and gender of facial…

cs.CV2022

VMRF: View Matching Neural Radiance Fields

Jiahui Zhang, Fangneng Zhan, Rongliang Wu +5

Neural Radiance Fields (NeRF) have demonstrated very impressive performance in novel view synthesis via implicitly modelling 3D representations from multi-view 2D images. However,…

cs.CV2022★ 2 cited

Marginal Contrastive Correspondence for Guided Image Generation

Fangneng Zhan, Yingchen Yu, Rongliang Wu +3

Exemplar-based image translation establishes dense correspondences between a conditional input and an exemplar (from two different domains) for leveraging detailed exemplar styles…

cs.CV2022

Fourier Document Restoration for Robust Document Dewarping and Recognition

Chuhui Xue, Zichen Tian, Fangneng Zhan +2

State-of-the-art document dewarping techniques learn to predict 3-dimensional information of documents which are prone to errors while dealing with documents with irregular distort…