7 papers · 1 filter
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…
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…
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…
D-FCGS: Feedforward Compression of Dynamic Gaussian Splatting for Free-Viewpoint Videos
Wenkang Zhang, Yan Zhao, Qiang Wang +3
Free-Viewpoint Video (FVV) enables immersive 3D experiences, but efficient compression of dynamic 3D representation remains a major challenge. Existing dynamic 3D Gaussian Splattin…
DualComp: End-to-End Learning of a Unified Dual-Modality Lossless Compressor
Yan Zhao, Zhengxue Cheng, Junxuan Zhang +3
Most learning-based lossless compressors are designed for a single modality, requiring separate models for multi-modal data and lacking flexibility. However, different modalities v…
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-Resolution
Xinning Chai, Yao Zhang, Yuxuan Zhang +4
Convolutional neural networks (CNNs) have been widely used in efficient image super-resolution. However, for CNN-based methods, performance gains often require deeper networks and…