12 citations · 16 across the 19 of their papers we have counts for
20 papers
CompactSplat: Spatially Adaptive Gaussian Distribution for Feedforward Scene Reconstruction
Bing He, Jingnan Gao, Yunuo Chen +4
Reconstructing 3D scenes from sparse views without per-scene optimization remains highly challenging, especially for recovering accurate geometry and fine textures. While recent fe…
Decoupled Self-Forcing Distillation for Streaming Talking Head Generation
Yanru An, Ruiyan Wang, Wenwu Wei +7
Streaming talking-head generation produces each frame as its driving audio arrives, yet fidelity and efficiency have so far pulled in opposite directions: end-to-end methods condit…
Full-4D: Generating Full-Scope 4D Scenes from a Single-View Video
Tingxi Chen, Ke Hao, Yabo Chen +6
Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Exis…
DP-DeGauss: Dynamic Probabilistic Gaussian Decomposition for Egocentric 4D Scene Reconstruction
Tingxi Chen, Zhengxue Cheng, Houqiang Zhong +3
Egocentric video is crucial for next-generation 4D scene reconstruction, with applications in AR/VR and embodied AI. However, reconstructing dynamic first-person scenes is challeng…
Joint Degradation-Aware Arbitrary-Scale Super-Resolution for Variable-Rate Extreme Image Compression
Xinning Chai, Zhengxue Cheng, Xin Li +2
Recent diffusion-based extreme image compression methods have demonstrated remarkable performance at ultra-low bitrates. However, most approaches require training separate diffusio…
OmniScaleSR: Unleashing Scale-Controlled Diffusion Prior for Faithful and Realistic Arbitrary-Scale Image Super-Resolution
Xinning Chai, Zhengxue Cheng, Yuhong Zhang +5
Arbitrary-scale super-resolution (ASSR) overcomes the limitation of traditional super-resolution (SR) methods that operate only at fixed scales (e.g., 4x), enabling a single model…
FreeInsert: Personalized Object Insertion with Geometric and Style Control
Yuhong Zhang, Han Wang, Yiwen Wang +2
Text-to-image diffusion models have made significant progress in image generation, allowing for effortless customized generation. However, existing image editing methods still face…
SemanticGarment: Semantic-Controlled Generation and Editing of 3D Gaussian Garments
Ruiyan Wang, Zhengxue Cheng, Zonghao Lin +5
3D digital garment generation and editing play a pivotal role in fashion design, virtual try-on, and gaming. Traditional methods struggle to meet the growing demand due to technica…
PA-HOI: A Physics-Aware Human and Object Interaction Dataset
Ruiyan Wang, Lin Zuo, Zonghao Lin +5
The Human-Object Interaction (HOI) task explores the dynamic interactions between humans and objects in physical environments, providing essential biomechanical and cognitive-behav…
Semantic and Temporal Integration in Latent Diffusion Space for High-Fidelity Video Super-Resolution
Yiwen Wang, Xinning Chai, Yuhong Zhang +4
Recent advancements in video super-resolution (VSR) models have demonstrated impressive results in enhancing low-resolution videos. However, due to limitations in adequately contro…
Enhanced Semantic Extraction and Guidance for UGC Image Super Resolution
Yiwen Wang, Ying Liang, Yuxuan Zhang +6
Due to the disparity between real-world degradations in user-generated content(UGC) images and synthetic degradations, traditional super-resolution methods struggle to generalize e…
Face De-identification: State-of-the-art Methods and Comparative Studies
Jingyi Cao, Xiangyi Chen, Bo Liu +5
The widespread use of image acquisition technologies, along with advances in facial recognition, has raised serious privacy concerns. Face de-identification usually refers to the p…
PoseTalk: Text-and-Audio-based Pose Control and Motion Refinement for One-Shot Talking Head Generation
Jun Ling, Yiwen Wang, Han Xue +2
While previous audio-driven talking head generation (THG) methods generate head poses from driving audio, the generated poses or lips cannot match the audio well or are not editabl…
A New People-Object Interaction Dataset and NVS Benchmarks
Shuai Guo, Houqiang Zhong, Qiuwen Wang +6
Recently, NVS in human-object interaction scenes has received increasing attention. Existing human-object interaction datasets mainly consist of static data with limited views, off…
H3D-DGS: Exploring Heterogeneous 3D Motion Representation for Deformable 3D Gaussian Splatting
Bing He, Yunuo Chen, Guo Lu +5
Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time render…
Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration
Yuhong Zhang, Hengsheng Zhang, Xinning Chai +4
Image restoration is a classic low-level problem aimed at recovering high-quality images from low-quality images with various degradations such as blur, noise, rain, haze, etc. How…
SSP-IR: Semantic and Structure Priors for Diffusion-based Realistic Image Restoration
Yuhong Zhang, Hengsheng Zhang, Zhengxue Cheng +3
Realistic image restoration is a crucial task in computer vision, and diffusion-based models for image restoration have garnered significant attention due to their ability to produ…
Multimodal Semantic-Aware Automatic Colorization with Diffusion Prior
Han Wang, Xinning Chai, Yiwen Wang +3
Colorizing grayscale images offers an engaging visual experience. Existing automatic colorization methods often fail to generate satisfactory results due to incorrect semantic colo…
Depth-Guided Robust and Fast Point Cloud Fusion NeRF for Sparse Input Views
Shuai Guo, Qiuwen Wang, Yijie Gao +2
Novel-view synthesis with sparse input views is important for real-world applications like AR/VR and autonomous driving. Recent methods have integrated depth information into NeRFs…
Disentangled Clothed Avatar Generation from Text Descriptions
Jionghao Wang, Yuan Liu, Zhiyang Dou +7
In this paper, we introduce a novel text-to-avatar generation method that separately generates the human body and the clothes and allows high-quality animation on the generated ava…