Search Results for author: Jiacheng Chen

Found 22 papers, 12 papers with code

MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mapping

no code implementations23 Mar 2024 Jiacheng Chen, Yuefan Wu, Jiaqi Tan, Hang Ma, Yasutaka Furukawa

The paper further makes benchmark contributions by 1) Improving processing code for existing datasets to produce consistent ground truth with temporal alignments and 2) Augmenting existing mAP metrics with consistency checks.

LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation

no code implementations2 Mar 2024 Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Guojun Peng, Zhiguang Cao, Yining Ma, Yue-Jiao Gong

Recent research explores optimization using large language models (LLMs) by either iteratively seeking next-step solutions from LLMs or directly prompting LLMs for an optimizer.

Code Generation Contrastive Learning

MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction

no code implementations20 Feb 2024 Shitao Tang, Jiacheng Chen, Dilin Wang, Chengzhou Tang, Fuyang Zhang, Yuchen Fan, Vikas Chandra, Yasutaka Furukawa, Rakesh Ranjan

MVDiffusion++ achieves superior flexibility and scalability with two surprisingly simple ideas: 1) A ``pose-free architecture'' where standard self-attention among 2D latent features learns 3D consistency across an arbitrary number of conditional and generation views without explicitly using camera pose information; and 2) A ``view dropout strategy'' that discards a substantial number of output views during training, which reduces the training-time memory footprint and enables dense and high-resolution view synthesis at test time.

3D Object Reconstruction 3D Reconstruction +2

Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning

1 code implementation4 Feb 2024 Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong

Recent Meta-learning for Black-Box Optimization (MetaBBO) methods harness neural networks to meta-learn configurations of traditional black-box optimizers.

Meta-Learning Zero-shot Generalization

Toward a Reinforcement-Learning-Based System for Adjusting Medication to Minimize Speech Disfluency

no code implementations12 Dec 2023 Pavlos Constas, Vikram Rawal, Matthew Honorio Oliveira, Andreas Constas, Aditya Khan, Kaison Cheung, Najma Sultani, Carrie Chen, Micol Altomare, Michael Akzam, Jiacheng Chen, Vhea He, Lauren Altomare, Heraa Murqi, Asad Khan, Nimit Amikumar Bhanshali, Youssef Rachad, Michael Guerzhoy

We propose a reinforcement learning (RL)-based system that would automatically prescribe a hypothetical patient medication that may help the patient with their mental health-related speech disfluency, and adjust the medication and the dosages in response to zero-cost frequent measurement of the fluency of the patient.

reinforcement-learning Reinforcement Learning (RL)

Channel-Feedback-Free Transmission for Downlink FD-RAN: A Radio Map based Complex-valued Precoding Network Approach

no code implementations30 Nov 2023 Jiwei Zhao, Jiacheng Chen, Zeyu Sun, Yuhang Shi, Haibo Zhou, Xuemin, Shen

As the demand for high-quality services proliferates, an innovative network architecture, the fully-decoupled RAN (FD-RAN), has emerged for more flexible spectrum resource utilization and lower network costs.

MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning

1 code implementation NeurIPS 2023 Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Zhenrui Li, Guojun Peng, Yue-Jiao Gong, Yining Ma, Zhiguang Cao

To fill this gap, we introduce MetaBox, the first benchmark platform expressly tailored for developing and evaluating MetaBBO-RL methods.

Benchmarking

MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion

1 code implementation NeurIPS 2023 Shitao Tang, Fuyang Zhang, Jiacheng Chen, Peng Wang, Yasutaka Furukawa

This paper introduces MVDiffusion, a simple yet effective method for generating consistent multi-view images from text prompts given pixel-to-pixel correspondences (e. g., perspective crops from a panorama or multi-view images given depth maps and poses).

Image Generation

PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models

1 code implementation NeurIPS 2023 Jiacheng Chen, Ruizhi Deng, Yasutaka Furukawa

This paper presents PolyDiffuse, a novel structured reconstruction algorithm that transforms visual sensor data into polygonal shapes with Diffusion Models (DM), an emerging machinery amid exploding generative AI, while formulating reconstruction as a generation process conditioned on sensor data.

PixMIM: Rethinking Pixel Reconstruction in Masked Image Modeling

1 code implementation4 Mar 2023 YuAn Liu, Songyang Zhang, Jiacheng Chen, Kai Chen, Dahua Lin

Masked Image Modeling (MIM) has achieved promising progress with the advent of Masked Autoencoders (MAE) and BEiT.

Self-Supervised Learning

HEAT: Holistic Edge Attention Transformer for Structured Reconstruction

1 code implementation CVPR 2022 Jiacheng Chen, Yiming Qian, Yasutaka Furukawa

This paper presents a novel attention-based neural network for structured reconstruction, which takes a 2D raster image as an input and reconstructs a planar graph depicting an underlying geometric structure.

Edge Classification Extracting Buildings In Remote Sensing Images +1

APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation

no code implementations24 Nov 2021 Jiacheng Chen, Bin-Bin Gao, Zongqing Lu, Jing-Hao Xue, Chengjie Wang, Qingmin Liao

In practice, it can adaptively generate multiple class-agnostic prototypes for query images and learn feature alignment in a self-contrastive manner.

Few-Shot Semantic Segmentation Metric Learning +2

Adaptive Appearance Rendering

1 code implementation24 Apr 2021 Mengyao Zhai, Ruizhi Deng, Jiacheng Chen, Lei Chen, Zhiwei Deng, Greg Mori

Hence, we develop an approach based on intermediate representations of poses and appearance: our pose-guided appearance rendering network firstly encodes the targets' poses using an encoder-decoder neural network.

Video Generation

SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes

no code implementations19 Apr 2021 Jiacheng Chen, Bin-Bin Gao, Zongqing Lu, Jing-Hao Xue, Chengjie Wang, Qingmin Liao

To this end, we generate self-contrastive background prototypes directly from the query image, with which we enable the construction of complete sample pairs and thus a complementary and auxiliary segmentation task to achieve the training of a better segmentation model.

Few-Shot Semantic Segmentation Metric Learning +2

Learning the Best Pooling Strategy for Visual Semantic Embedding

1 code implementation CVPR 2021 Jiacheng Chen, Hexiang Hu, Hao Wu, Yuning Jiang, Changhu Wang

Visual Semantic Embedding (VSE) is a dominant approach for vision-language retrieval, which aims at learning a deep embedding space such that visual data are embedded close to their semantic text labels or descriptions.

Cross-Modal Information Retrieval Retrieval +3

BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps

1 code implementation ACL 2020 Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha

To this end, we propose BabyWalk, a new VLN agent that is learned to navigate by decomposing long instructions into shorter ones (BabySteps) and completing them sequentially.

Imitation Learning Navigate +1

Floor-SP: Inverse CAD for Floorplans by Sequential Room-wise Shortest Path

1 code implementation ICCV 2019 Jiacheng Chen, Chen Liu, Jiaye Wu, Yasutaka Furukawa

This paper proposes a new approach for automated floorplan reconstruction from RGBD scans, a major milestone in indoor mapping research.

Edge Detection

Learning to Forecast Videos of Human Activity with Multi-granularity Models and Adaptive Rendering

no code implementations5 Dec 2017 Mengyao Zhai, Jiacheng Chen, Ruizhi Deng, Lei Chen, Ligeng Zhu, Greg Mori

An architecture combining a hierarchical temporal model for predicting human poses and encoder-decoder convolutional neural networks for rendering target appearances is proposed.

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