Search Results for author: Weifeng Chen

Found 14 papers, 4 papers with code

ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling

no code implementations9 Feb 2024 Siming Yan, Min Bai, Weifeng Chen, Xiong Zhou, QiXing Huang, Li Erran Li

By combining natural language understanding and the generation capabilities and breadth of knowledge of large language models with image perception, recent large vision language models (LVLMs) have shown unprecedented reasoning capabilities in the real world.

Natural Language Understanding Visual Grounding

DiffusionGPT: LLM-Driven Text-to-Image Generation System

no code implementations18 Jan 2024 Jie Qin, Jie Wu, Weifeng Chen, Yuxi Ren, Huixia Li, Hefeng Wu, Xuefeng Xiao, Rui Wang, Shilei Wen

Diffusion models have opened up new avenues for the field of image generation, resulting in the proliferation of high-quality models shared on open-source platforms.

Model Selection Text-to-Image Generation

Control-A-Video: Controllable Text-to-Video Generation with Diffusion Models

1 code implementation23 May 2023 Weifeng Chen, Yatai Ji, Jie Wu, Hefeng Wu, Pan Xie, Jiashi Li, Xin Xia, Xuefeng Xiao, Liang Lin

Based on a pre-trained conditional text-to-image (T2I) diffusion model, our model aims to generate videos conditioned on a sequence of control signals, such as edge or depth maps.

Optical Flow Estimation Style Transfer +4

MSRL: Distributed Reinforcement Learning with Dataflow Fragments

no code implementations3 Oct 2022 Huanzhou Zhu, Bo Zhao, Gang Chen, Weifeng Chen, Yijie Chen, Liang Shi, Yaodong Yang, Peter Pietzuch, Lei Chen

Yet, current distributed RL systems tie the definition of RL algorithms to their distributed execution: they hard-code particular distribution strategies and only accelerate specific parts of the computation (e. g. policy network updates) on GPU workers.

reinforcement-learning Reinforcement Learning (RL)

HYPE-C: Evaluating Image Completion Models Through Standardized Crowdsourcing

no code implementations1 Jan 2021 Emily Walters, Weifeng Chen, Jia Deng

Recent work has proposed the use of human evaluation for image synthesis models, allowing for a reliable method to evaluate the visual quality of generated images.

Image Generation

OASIS: A Large-Scale Dataset for Single Image 3D in the Wild

no code implementations CVPR 2020 Weifeng Chen, Shengyi Qian, David Fan, Noriyuki Kojima, Max Hamilton, Jia Deng

Single-view 3D is the task of recovering 3D properties such as depth and surface normals from a single image.

Surface Normals in the Wild

no code implementations ICCV 2017 Weifeng Chen, Donglai Xiang, Jia Deng

We study the problem of single-image depth estimation for images in the wild.

Depth Estimation

Single-Image Depth Perception in the Wild

4 code implementations NeurIPS 2016 Weifeng Chen, Zhao Fu, Dawei Yang, Jia Deng

This paper studies single-image depth perception in the wild, i. e., recovering depth from a single image taken in unconstrained settings.

Depth Estimation

Cannot find the paper you are looking for? You can Submit a new open access paper.