Hao Zhang

Orcid: 0000-0001-8232-1665

Affiliations:
  • Hong Kong University of Science and Technology, Guangzhou, China
  • International Digital Economy Academy (IDEA), China


According to our database1, Hao Zhang authored at least 34 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
DN-DETR: Accelerate DETR Training by Introducing Query DeNoising.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024

MotionLLM: Understanding Human Behaviors from Human Motions and Videos.
CoRR, 2024

Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection.
CoRR, 2024

Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.
CoRR, 2024

LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models.
Proceedings of the Computer Vision - ECCV 2024, 2024

Grounding DINO: Marrying DINO with Grounded Pre-training for Open-Set Object Detection.
Proceedings of the Computer Vision - ECCV 2024, 2024

LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents.
Proceedings of the Computer Vision - ECCV 2024, 2024

Segment and Recognize Anything at Any Granularity.
Proceedings of the Computer Vision - ECCV 2024, 2024

TAPTR: Tracking Any Point with Transformers as Detection.
Proceedings of the Computer Vision - ECCV 2024, 2024

Visual in-Context Prompting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Interfacing Foundation Models' Embeddings.
CoRR, 2023

LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models.
CoRR, 2023

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.
CoRR, 2023

Semantic-SAM: Segment and Recognize Anything at Any Granularity.
CoRR, 2023

detrex: Benchmarking Detection Transformers.
CoRR, 2023

A Strong and Reproducible Object Detector with Only Public Datasets.
CoRR, 2023

Segment Everything Everywhere All at Once.
CoRR, 2023

A Simple Framework for Open-Vocabulary Segmentation and Detection.
CoRR, 2023

Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
CoRR, 2023

DA-BEV: Depth Aware BEV Transformer for 3D Object Detection.
CoRR, 2023

Segment Everything Everywhere All at Once.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Simple Framework for Open-Vocabulary Segmentation and Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Detection Transformer with Stable Matching.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

DFA3D: 3D Deformable Attention For 2D-to-3D Feature Lifting.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

MP-Former: Mask-Piloted Transformer for Image Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Unified Mutual Supervision Framework for Referring Expression Segmentation and Generation.
CoRR, 2022

Active Domain Adaptation with Multi-level Contrastive Units for Semantic Segmentation.
CoRR, 2022

Vision-Language Intelligence: Tasks, Representation Learning, and Large Models.
CoRR, 2022

DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Active Domain Adaptation with Multi-level Contrastive Units for Semantic Segmentation.
Proceedings of the Computer Vision - ACCV 2022, 2022


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