b'Peng Gao'

research

∙ 09/19/2023

Bridging Zero-shot Object Navigation and Foundation Models through Pixel-Guided Navigation Skill

Zero-shot object navigation is a challenging task for home-assistance ro...

0 Wenzhe Cai, et al. ∙

research

∙ 09/15/2023

MTG: Mapless Trajectory Generator with Traversability Coverage for Outdoor Navigation

We present a novel learning algorithm for trajectory generation for outd...

0 Jing Liang, et al. ∙

research

∙ 09/07/2023

ImageBind-LLM: Multi-modality Instruction Tuning

We present ImageBind-LLM, a multi-modality instruction tuning method of ...

0 Jiaming Han, et al. ∙

research

∙ 09/01/2023

Point-Bind Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following

We introduce Point-Bind, a 3D multi-modality model aligning point clouds...

0 Ziyu Guo, et al. ∙

research

∙ 08/25/2023

OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Large language models (LLMs) have revolutionized natural language proces...

0 Wenqi Shao, et al. ∙

research

∙ 08/07/2023

Tiny LVLM-eHub: Early Multimodal Experiments with Bard

Recent advancements in Large Vision-Language Models (LVLMs) have demonst...

0 Wenqi Shao, et al. ∙

research

∙ 06/28/2023

Enhanced Neural Beamformer with Spatial Information for Target Speech Extraction

Recently, deep learning-based beamforming algorithms have shown promisin...

0 Aoqi Guo, et al. ∙

research

∙ 06/15/2023

LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models

Large Vision-Language Models (LVLMs) have recently played a dominant rol...

0 Peng Xu, et al. ∙

research

∙ 05/25/2023

Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation

Recently, video object segmentation (VOS) referred by multi-modal signal...

0 Shilin Yan, et al. ∙

research

∙ 05/18/2023

Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model

Foundation models have made significant strides in various applications,...

3 Siyuan Huang, et al. ∙

research

∙ 05/16/2023

SUG: Single-dataset Unified Generalization for 3D Point Cloud Classification

Although Domain Generalization (DG) problem has been fast-growing in the...

0 Siyuan Huang, et al. ∙

research

∙ 05/04/2023

Personalize Segment Anything Model with One Shot

Driven by large-data pre-training, Segment Anything Model (SAM) has been...

4 Renrui Zhang, et al. ∙

research

∙ 04/28/2023

LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

How to efficiently transform large language models (LLMs) into instructi...

1 Peng Gao, et al. ∙

research

∙ 04/26/2023

Filter Pruning via Filters Similarity in Consecutive Layers

Filter pruning is widely adopted to compress and accelerate the Convolut...

0 Xiaorui Wang, et al. ∙

research

∙ 04/24/2023

OGMN: Occlusion-guided Multi-task Network for Object Detection in UAV Images

Occlusion between objects is one of the overlooked challenges for object...

0 Xuexue Li, et al. ∙

research

∙ 04/03/2023

Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior Refinement

The popularity of Contrastive Language-Image Pre-training (CLIP) has pro...

0 Xiangyang Zhu, et al. ∙

research

∙ 04/01/2023

Q-DETR: An Efficient Low-Bit Quantized Detection Transformer

The recent detection transformer (DETR) has advanced object detection, b...

0 Sheng Xu, et al. ∙

research

∙ 03/28/2023

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

We present LLaMA-Adapter, a lightweight adaption method to efficiently f...

1 Renrui Zhang, et al. ∙

research

∙ 03/20/2023

Exploring Representation Learning for Small-Footprint Keyword Spotting

In this paper, we investigate representation learning for low-resource k...

0 Fan Cui, et al. ∙

research

∙ 03/14/2023

Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis

We present a Non-parametric Network for 3D point cloud analysis, Point-N...

0 Renrui Zhang, et al. ∙

research

∙ 03/09/2023

Mimic before Reconstruct: Enhancing Masked Autoencoders with Feature Mimicking

Masked Autoencoders (MAE) have been popular paradigms for large-scale vi...

0 Peng Gao, et al. ∙

research

∙ 03/03/2023

Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners

Visual recognition in low-data regimes requires deep neural networks to ...

0 Renrui Zhang, et al. ∙

research

∙ 03/02/2023

FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature Augmentation

One-to-one matching is a crucial design in DETR-like object detection fr...

0 Rongyao Fang, et al. ∙

research

∙ 02/02/2023

Resilient Binary Neural Network

Binary neural networks (BNNs) have received ever-increasing popularity f...

0 Sheng Xu, et al. ∙

research

∙ 12/20/2022

ThreatKG: A Threat Knowledge Graph for Automated Open-Source Cyber Threat Intelligence Gathering and Management

Despite the increased adoption of open-source cyber threat intelligence ...

0 Peng Gao, et al. ∙

research

∙ 12/19/2022

An Efficient Drug-Drug Interactions Prediction Technology for Molecularly Intelligent Manufacturing

Drug-Drug Interactions (DDIs) prediction is an essential issue in the mo...

0 Peng Gao, et al. ∙

research

∙ 12/13/2022

Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders

Pre-training by numerous image data has become de-facto for robust 2D re...

0 Renrui Zhang, et al. ∙

research

∙ 11/21/2022

PointCLIP V2: Adapting CLIP for Powerful 3D Open-world Learning

Contrastive Language-Image Pre-training (CLIP) has shown promising open-...

0 Xiangyang Zhu, et al. ∙

research

∙ 11/16/2022

Stare at What You See: Masked Image Modeling without Reconstruction

Masked Autoencoders (MAE) have been prevailing paradigms for large-scale...

0 Hongwei Xue, et al. ∙

research

∙ 11/10/2022

Zebra: Deeply Integrating System-Level Provenance Search and Tracking for Efficient Attack Investigation

System auditing has emerged as a key approach for monitoring system call...

3 Xinyu Yang, et al. ∙

research

∙ 10/21/2022

HCL: Improving Graph Representation with Hierarchical Contrastive Learning

Contrastive learning has emerged as a powerful tool for graph representa...

0 Jun Wang, et al. ∙

research

∙ 10/13/2022

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

The large pre-trained vision transformers (ViTs) have demonstrated remar...

0 Yanjing Li, et al. ∙

research

∙ 10/07/2022

IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors

Knowledge distillation (KD) has been proven to be useful for training co...

0 Sheng Xu, et al. ∙

research

∙ 09/25/2022

Collaboration of Pre-trained Models Makes Better Few-shot Learner

Few-shot classification requires deep neural networks to learn generaliz...

28 Renrui Zhang, et al. ∙

research

∙ 09/04/2022

Recurrent Bilinear Optimization for Binary Neural Networks

Binary Neural Networks (BNNs) show great promise for real-world embedded...

0 Sheng Xu, et al. ∙

research

∙ 08/06/2022

Frozen CLIP Models are Efficient Video Learners

Video recognition has been dominated by the end-to-end learning paradigm...

0 Ziyi Lin, et al. ∙

research

∙ 07/19/2022

Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification

Contrastive Vision-Language Pre-training, known as CLIP, has provided a ...

0 Renrui Zhang, et al. ∙

research

∙ 07/14/2022

Prototypical Contrast Adaptation for Domain Adaptive Semantic Segmentation

Unsupervised Domain Adaptation (UDA) aims to adapt the model trained on ...

9 Zhengkai Jiang, et al. ∙

research

∙ 05/30/2022

Illumination Adaptive Transformer

Challenging illumination conditions (low light, underexposure and overex...

0 Ziteng Cui, et al. ∙

research

∙ 05/29/2022

SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models

Large scale pre-training models have been widely used in named entity re...

0 Changyu Hou, et al. ∙

research

∙ 05/28/2022

Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training

Masked Autoencoders (MAE) have shown great potentials in self-supervised...

0 Renrui Zhang, et al. ∙

research

∙ 05/20/2022

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission...

0 Yang Yang, et al. ∙

research

∙ 05/18/2022

PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking

This paper describes the PASH participation in TREC 2021 Deep Learning T...

0 Yixuan Qiao, et al. ∙

research

∙ 05/08/2022

ConvMAE: Masked Convolution Meets Masked Autoencoders

Vision Transformers (ViT) become widely-adopted architectures for variou...

0 Peng Gao, et al. ∙

research

∙ 04/03/2022

POS-BERT: Point Cloud One-Stage BERT Pre-Training

Recently, the pre-training paradigm combining Transformer and masked lan...

0 Kexue Fu, et al. ∙

research

∙ 03/31/2022

Learning Decoupling Features Through Orthogonality Regularization

Keyword spotting (KWS) and speaker verification (SV) are two important t...

0 Li Wang, et al. ∙

research

∙ 03/24/2022

MonoDETR: Depth-aware Transformer for Monocular 3D Object Detection

Monocular 3D object detection has long been a challenging task in autono...

0 Renrui Zhang, et al. ∙

research

∙ 03/02/2022

CandidateDrug4Cancer: An Open Molecular Graph Learning Benchmark on Drug Discovery for Cancer

Anti-cancer drug discoveries have been serendipitous, we sought to prese...

0 Xianbin Ye, et al. ∙

research

∙ 02/09/2022

Distillation with Contrast is All You Need for Self-Supervised Point Cloud Representation Learning

In this paper, we propose a simple and general framework for self-superv...

0 Kexue Fu, et al. ∙

research

∙ 01/24/2022

UniFormer: Unifying Convolution and Self-attention for Visual Recognition

It is a challenging task to learn discriminative representation from ima...

7 Kunchang Li, et al. ∙

Peng Gao

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