most citedHarnessing Low-Frequency Neural Fields for Few-Shot View Synthesis

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

PanoFree: Tuning-Free Holistic Multi-view Image Generation with Cross-view Self-Guidance

Aoming Liu, Zhong Li, Zhang Chen +3

Immersive scene generation, notably panorama creation, benefits significantly from the adaptation of large pre-trained text-to-image (T2I) models for multi-view image generation. D…

cs.CL20241 cited

TechGPT-2.0: A large language model project to solve the task of knowledge graph construction

Jiaqi Wang, Yuying Chang, Zhong Li +6

Large language models have exhibited robust performance across diverse natural language processing tasks. This report introduces TechGPT-2.0, a project designed to enhance the capa…

cs.CV2023

Relit-NeuLF: Efficient Relighting and Novel View Synthesis via Neural 4D Light Field

Zhong Li, Liangchen Song, Zhang Chen +4

In this paper, we address the problem of simultaneous relighting and novel view synthesis of a complex scene from multi-view images with a limited number of light sources. We propo…

cs.CV2023

NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions

Zhang Chen, Zhong Li, Liangchen Song +4

We present a novel type of neural fields that uses general radial bases for signal representation. State-of-the-art neural fields typically rely on grid-based representations for s…

cs.CV20234 cited

Harnessing Low-Frequency Neural Fields for Few-Shot View Synthesis

Liangchen Song, Zhong Li, Xuan Gong +4

Neural Radiance Fields (NeRF) have led to breakthroughs in the novel view synthesis problem. Positional Encoding (P.E.) is a critical factor that brings the impressive performance…