Search Results for author: Ziyu Wan

Found 18 papers, 12 papers with code

Natural Language Reinforcement Learning

no code implementations11 Feb 2024 Xidong Feng, Ziyu Wan, Mengyue Yang, Ziyan Wang, Girish A. Koushik, Yali Du, Ying Wen, Jun Wang

Reinforcement Learning (RL) has shown remarkable abilities in learning policies for decision-making tasks.

Decision Making reinforcement-learning +1

HeadArtist: Text-conditioned 3D Head Generation with Self Score Distillation

no code implementations12 Dec 2023 Hongyu Liu, Xuan Wang, Ziyu Wan, Yujun Shen, Yibing Song, Jing Liao, Qifeng Chen

The noisy image, landmarks, and text condition are then fed into the frozen ControlNet twice for noise prediction.

CAD: Photorealistic 3D Generation via Adversarial Distillation

no code implementations11 Dec 2023 Ziyu Wan, Despoina Paschalidou, IAn Huang, Hongyu Liu, Bokui Shen, Xiaoyu Xiang, Jing Liao, Leonidas Guibas

The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects.

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

1 code implementation29 Sep 2023 Xidong Feng, Ziyu Wan, Muning Wen, Stephen Marcus McAleer, Ying Wen, Weinan Zhang, Jun Wang

Empirical results across reasoning, planning, alignment, and decision-making tasks show that TS-LLM outperforms existing approaches and can handle trees with a depth of 64.

Decision Making Language Modelling +1

Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields

1 code implementation19 May 2023 Jingbo Zhang, Xiaoyu Li, Ziyu Wan, Can Wang, Jing Liao

Extensive experiments demonstrate that our Text2NeRF outperforms existing methods in producing photo-realistic, multi-view consistent, and diverse 3D scenes from a variety of natural language prompts.

3D Reconstruction Monocular Depth Estimation +3

Order Matters: Agent-by-agent Policy Optimization

no code implementations13 Feb 2023 Xihuai Wang, Zheng Tian, Ziyu Wan, Ying Wen, Jun Wang, Weinan Zhang

In this paper, we propose the \textbf{A}gent-by-\textbf{a}gent \textbf{P}olicy \textbf{O}ptimization (A2PO) algorithm to improve the sample efficiency and retain the guarantees of monotonic improvement for each agent during training.

On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective

1 code implementation24 Dec 2022 Ying Wen, Ziyu Wan, Ming Zhou, Shufang Hou, Zhe Cao, Chenyang Le, Jingxiao Chen, Zheng Tian, Weinan Zhang, Jun Wang

The pervasive uncertainty and dynamic nature of real-world environments present significant challenges for the widespread implementation of machine-driven Intelligent Decision-Making (IDM) systems.

Decision Making Image Captioning +2

Adaptive Joint Optimization for 3D Reconstruction with Differentiable Rendering

no code implementations15 Aug 2022 Jingbo Zhang, Ziyu Wan, Jing Liao

Due to inevitable noises introduced during scanning and quantization, 3D reconstruction via RGB-D sensors suffers from errors both in geometry and texture, leading to artifacts such as camera drifting, mesh distortion, texture ghosting, and blurriness.

3D Reconstruction Quantization

FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing

1 code implementation11 Aug 2022 Jingbo Zhang, Xiaoyu Li, Ziyu Wan, Can Wang, Jing Liao

Unlike existing dynamic NeRFs that require dense images as input and can only be modeled for a single identity, our method enables face reconstruction across different persons with few-shot inputs.

3D Face Reconstruction

Bringing Old Films Back to Life

1 code implementation CVPR 2022 Ziyu Wan, Bo Zhang, Dongdong Chen, Jing Liao

We present a learning-based framework, recurrent transformer network (RTN), to restore heavily degraded old films.

Analog Video Restoration

Neural Auto-Curricula in Two-Player Zero-Sum Games

1 code implementation NeurIPS 2021 Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen Mcaleer, Ying Wen, Jun Wang, Yaodong Yang

When solving two-player zero-sum games, multi-agent reinforcement learning (MARL) algorithms often create populations of agents where, at each iteration, a new agent is discovered as the best response to a mixture over the opponent population.

Multi-agent Reinforcement Learning Vocal Bursts Valence Prediction

MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning

1 code implementation5 Jun 2021 Ming Zhou, Ziyu Wan, Hanjing Wang, Muning Wen, Runzhe Wu, Ying Wen, Yaodong Yang, Weinan Zhang, Jun Wang

Our framework is comprised of three key components: (1) a centralized task dispatching model, which supports the self-generated tasks and scalable training with heterogeneous policy combinations; (2) a programming architecture named Actor-Evaluator-Learner, which achieves high parallelism for both training and sampling, and meets the evaluation requirement of auto-curriculum learning; (3) a higher-level abstraction of MARL training paradigms, which enables efficient code reuse and flexible deployments on different distributed computing paradigms.

Atari Games Distributed Computing +3

Neural Auto-Curricula

1 code implementation4 Jun 2021 Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen Mcaleer, Ying Wen, Jun Wang, Yaodong Yang

When solving two-player zero-sum games, multi-agent reinforcement learning (MARL) algorithms often create populations of agents where, at each iteration, a new agent is discovered as the best response to a mixture over the opponent population.

Multi-agent Reinforcement Learning

PD-GAN: Probabilistic Diverse GAN for Image Inpainting

1 code implementation CVPR 2021 Hongyu Liu, Ziyu Wan, Wei Huang, Yibing Song, Xintong Han, Jing Liao

To this end, we propose spatially probabilistic diversity normalization (SPDNorm) inside the modulation to model the probability of generating a pixel conditioned on the context information.

Image Inpainting Image Restoration

High-Fidelity Pluralistic Image Completion with Transformers

4 code implementations ICCV 2021 Ziyu Wan, Jingbo Zhang, Dongdong Chen, Jing Liao

Image completion has made tremendous progress with convolutional neural networks (CNNs), because of their powerful texture modeling capacity.

Image Inpainting Vocal Bursts Intensity Prediction

DeFLOCNet: Deep Image Editing via Flexible Low-level Controls

1 code implementation CVPR 2021 Hongyu Liu, Ziyu Wan, Wei Huang, Yibing Song, Xintong Han, Jing Liao, Bing Jiang, Wei Liu

While existing methods combine an input image and these low-level controls for CNN inputs, the corresponding feature representations are not sufficient to convey user intentions, leading to unfaithfully generated content.

Texture Synthesis

Meta-PU: An Arbitrary-Scale Upsampling Network for Point Cloud

1 code implementation8 Feb 2021 Shuquan Ye, Dongdong Chen, Songfang Han, Ziyu Wan, Jing Liao

Thus, Meta-PU even outperforms the existing methods trained for a specific scale factor only.

Graphics

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