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...
share
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...
research
∙
09/07/2023
ImageBind-LLM: Multi-modality Instruction Tuning
We present ImageBind-LLM, a multi-modality instruction tuning method of ...
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...
research
∙
08/25/2023
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Large language models (LLMs) have revolutionized natural language proces...
research
∙
08/07/2023
Tiny LVLM-eHub: Early Multimodal Experiments with Bard
Recent advancements in Large Vision-Language Models (LVLMs) have demonst...
research
∙
06/28/2023
Enhanced Neural Beamformer with Spatial Information for Target Speech Extraction
Recently, deep learning-based beamforming algorithms have shown promisin...
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...
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...
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,...
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...
research
∙
05/04/2023
Personalize Segment Anything Model with One Shot
Driven by large-data pre-training, Segment Anything Model (SAM) has been...
research
∙
04/28/2023
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
How to efficiently transform large language models (LLMs) into instructi...
research
∙
04/26/2023
Filter Pruning via Filters Similarity in Consecutive Layers
Filter pruning is widely adopted to compress and accelerate the Convolut...
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...
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...
research
∙
04/01/2023
Q-DETR: An Efficient Low-Bit Quantized Detection Transformer
The recent detection transformer (DETR) has advanced object detection, b...
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...
research
∙
03/20/2023
Exploring Representation Learning for Small-Footprint Keyword Spotting
In this paper, we investigate representation learning for low-resource k...
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...
research
∙
03/09/2023
Mimic before Reconstruct: Enhancing Masked Autoencoders with Feature Mimicking
Masked Autoencoders (MAE) have been popular paradigms for large-scale vi...
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 ...
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...
research
∙
02/02/2023
Resilient Binary Neural Network
Binary neural networks (BNNs) have received ever-increasing popularity f...
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 ...
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...
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...
research
∙
11/21/2022
PointCLIP V2: Adapting CLIP for Powerful 3D Open-world Learning
Contrastive Language-Image Pre-training (CLIP) has shown promising open-...
research
∙
11/16/2022
Stare at What You See: Masked Image Modeling without Reconstruction
Masked Autoencoders (MAE) have been prevailing paradigms for large-scale...
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...
research
∙
10/21/2022
HCL: Improving Graph Representation with Hierarchical Contrastive Learning
Contrastive learning has emerged as a powerful tool for graph representa...
research
∙
10/13/2022
Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer
The large pre-trained vision transformers (ViTs) have demonstrated remar...
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...
research
∙
09/25/2022
Collaboration of Pre-trained Models Makes Better Few-shot Learner
Few-shot classification requires deep neural networks to learn generaliz...
research
∙
09/04/2022
Recurrent Bilinear Optimization for Binary Neural Networks
Binary Neural Networks (BNNs) show great promise for real-world embedded...
research
∙
08/06/2022
Frozen CLIP Models are Efficient Video Learners
Video recognition has been dominated by the end-to-end learning paradigm...
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 ...
research
∙
07/14/2022
Prototypical Contrast Adaptation for Domain Adaptive Semantic Segmentation
Unsupervised Domain Adaptation (UDA) aims to adapt the model trained on ...
research
∙
05/30/2022
Illumination Adaptive Transformer
Challenging illumination conditions (low light, underexposure and overex...
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...
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...
research
∙
05/20/2022
6G Network AI Architecture for Everyone-Centric Customized Services
Mobile communication standards were developed for enhancing transmission...
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...
research
∙
05/08/2022
ConvMAE: Masked Convolution Meets Masked Autoencoders
Vision Transformers (ViT) become widely-adopted architectures for variou...
research
∙
04/03/2022
POS-BERT: Point Cloud One-Stage BERT Pre-Training
Recently, the pre-training paradigm combining Transformer and masked lan...
research
∙
03/31/2022
Learning Decoupling Features Through Orthogonality Regularization
Keyword spotting (KWS) and speaker verification (SV) are two important t...
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...
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...
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...
research
∙
01/24/2022
