Search Results for author: Lingzhi Li

Found 10 papers, 6 papers with code

High-Resolution Volumetric Reconstruction for Clothed Humans

no code implementations25 Jul 2023 Sicong Tang, Guangyuan Wang, Qing Ran, Lingzhi Li, Li Shen, Ping Tan

We present a novel method for reconstructing clothed humans from a sparse set of, e. g., 1 to 6 RGB images.


Compact Real-time Radiance Fields with Neural Codebook

no code implementations29 May 2023 Lingzhi Li, Zhongshu Wang, Zhen Shen, Li Shen, Ping Tan

Reconstructing neural radiance fields with explicit volumetric representations, demonstrated by Plenoxels, has shown remarkable advantages on training and rendering efficiency, while grid-based representations typically induce considerable overhead for storage and transmission.

4K-NeRF: High Fidelity Neural Radiance Fields at Ultra High Resolutions

1 code implementation9 Dec 2022 Zhongshu Wang, Lingzhi Li, Zhen Shen, Li Shen, Liefeng Bo

In this paper, we present a novel and effective framework, named 4K-NeRF, to pursue high fidelity view synthesis on the challenging scenarios of ultra high resolutions, building on the methodology of neural radiance fields (NeRF).

Vocal Bursts Intensity Prediction

Compressing Volumetric Radiance Fields to 1 MB

1 code implementation CVPR 2023 Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen, Liefeng Bo

Approximating radiance fields with volumetric grids is one of promising directions for improving NeRF, represented by methods like Plenoxels and DVGO, which achieve super-fast training convergence and real-time rendering.

Model Compression Neural Rendering +1

Streaming Radiance Fields for 3D Video Synthesis

1 code implementation26 Oct 2022 Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen, Ping Tan

Instead of training a single model that combines all the frames, we formulate the dynamic modeling problem with an incremental learning paradigm in which per-frame model difference is trained to complement the adaption of a base model on the current frame.

Incremental Learning Model Optimization +1

FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping

8 code implementations31 Dec 2019 Lingzhi Li, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen

We propose a novel attributes encoder for extracting multi-level target face attributes, and a new generator with carefully designed Adaptive Attentional Denormalization (AAD) layers to adaptively integrate the identity and the attributes for face synthesis.

Face Generation Face Swapping +1

Face X-ray for More General Face Forgery Detection

4 code implementations CVPR 2020 Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, Baining Guo

For this reason, face X-ray provides an effective way for detecting forgery generated by most existing face manipulation algorithms.

DeepFake Detection Face Swapping

Context-Sensitive Generation of Open-Domain Conversational Responses

no code implementations COLING 2018 Wei-Nan Zhang, Yiming Cui, Yifa Wang, Qingfu Zhu, Lingzhi Li, Lianqiang Zhou, Ting Liu

Despite the success of existing works on single-turn conversation generation, taking the coherence in consideration, human conversing is actually a context-sensitive process.

Information Retrieval Machine Translation

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