10 papers
-Mesh: Reinforcement Learning Powered Mesh Reconstruction via Geometry and Appearance Refinement
Haoyang Wang, Liming Liu, Xinggong Zhang
Mesh reconstruction from Neural Radiance Fields (NeRF) is widely used in 3D reconstruction and has been applied across numerous domains. However, existing methods typically rely so…
HybridPrompt: Bridging Generative Priors and Traditional Codecs for Mobile Streaming
Liming Liu, Jiangkai Wu, Haoyang Wang +3
In Video on Demand (VoD) scenarios, traditional codecs are the industry standard due to their high decoding efficiency. However, they suffer from severe quality degradation under l…
Artic: AI-oriented Real-time Communication for MLLM Video Assistant
Jiangkai Wu, Zhiyuan Ren, Junquan Zhong +2
AI Video Assistant emerges as a new paradigm for Real-time Communication (RTC), where one peer is a Multimodal Large Language Model (MLLM) deployed in the cloud. This makes interac…
Smaller is Better: Generative Models Can Power Short Video Preloading
Liming Liu, Jiangkai Wu, Xinggong Zhang
Preloading is widely used in short video platforms to minimize playback stalls by downloading future content in advance. However, existing strategies face a tradeoff. Aggressive pr…
Morphe: High-Fidelity Generative Video Streaming with Vision Foundation Model
Tianyi Gong, Zijian Cao, Zixing Zhang +4
Video streaming is a fundamental Internet service, while the quality still cannot be guaranteed especially in poor network conditions such as bandwidth-constrained and remote areas…
R-Meshfusion: Reinforcement Learning Powered Sparse-View Mesh Reconstruction with Diffusion Priors
Haoyang Wang, Liming Liu, Peiheng Wang +3
Mesh reconstruction from multi-view images is a fundamental problem in computer vision, but its performance degrades significantly under sparse-view conditions, especially in unsee…