2 citations · 2 across the 16 of their papers we have counts for
19 papers
All Roads Lead to Rome: Flow-driven Multi-Anchor Exploration for Open-Environment Active 3D Mapping
Yang Li, Aming Wu, Zihao Zhang +3
To advance the development of embodied intelligence, Open-Environment Active 3D Mapping has attracted increasing attention, aiming to perform a long-horizon and shortest trajectory…
Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection
Zihao Zhang, Aming Wu, Yang Li +1
In this paper, we study Single-Domain Generalized Object Detection (Single-DGOD), which aims to transfer a detector trained on a single source domain to multiple unseen domains. Ex…
Geometric-Aware Hypergraph Reasoning for Novel Class Discovery in Point Cloud Segmentation
Zihao Zhang, Aming Wu, Yang Li +2
Novel class discovery in point cloud segmentation aims to transfer knowledge from known classes to automatically identify and segment unlabeled novel classes in point clouds. Exist…
Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation
Xitie Zhang, Aming Wu, Yahong Han
Cross-task generalization is a core challenge in open-world robotic manipulation, and the key lies in extracting transferable manipulation knowledge from seen tasks. Recent in-cont…
Towards Open Environments and Instructions: General Vision-Language Navigation via Fast-Slow Interactive Reasoning
Yang Li, Aming Wu, Zihao Zhang +1
Vision-Language Navigation (VLN) aims to enable agents to navigate to a target location based on language instructions. Traditional VLN often follows a close-set assumption, i.e.,…
How Order-Sensitive Are LLMs? OrderProbe for Deterministic Structural Reconstruction
Zhaolu Kang, Yingjie He, Kehan Jiang +18
Large language models (LLMs) excel at semantic understanding, yet their ability to reconstruct internal structure from scrambled inputs remains underexplored. Sentence-level restor…
Simulating Distribution Dynamics: Liquid Temporal Feature Evolution for Single-Domain Generalized Object Detection
Zihao Zhang, Yang Li, Aming Wu +1
In this paper, we focus on Single-Domain Generalized Object Detection (Single-DGOD), aiming to transfer a detector trained on one source domain to multiple unknown domains. Existin…
Mamba-driven multi-perspective structural understanding for molecular ground-state conformation prediction
Yuxin Gou, Aming Wu, Richang Hong +1
A comprehensive understanding of molecular structures is important for the prediction of molecular ground-state conformation involving property information. Meanwhile, state space…
Novel Class Discovery for Point Cloud Segmentation via Joint Learning of Causal Representation and Reasoning
Yang Li, Aming Wu, Zihao Zhang +1
In this paper, we focus on Novel Class Discovery for Point Cloud Segmentation (3D-NCD), aiming to learn a model that can segment unlabeled (novel) 3D classes using only the supervi…
Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios
Deng Li, Aming Wu, Yang Li +2
In practice, environments constantly change over time and space, posing significant challenges for object detectors trained based on a closed-set assumption, i.e., training and tes…
Style Evolving along Chain-of-Thought for Unknown-Domain Object Detection
Zihao Zhang, Aming Wu, Yahong Han
Recently, a task of Single-Domain Generalized Object Detection (Single-DGOD) is proposed, aiming to generalize a detector to multiple unknown domains never seen before during train…
Prompt-Driven Dynamic Object-Centric Learning for Single Domain Generalization
Deng Li, Aming Wu, Yaowei Wang +1
Single-domain generalization aims to learn a model from single source domain data to achieve generalized performance on other unseen target domains. Existing works primarily focus…
Environment-Invariant Curriculum Relation Learning for Fine-Grained Scene Graph Generation
Yukuan Min, Aming Wu, Cheng Deng
The scene graph generation (SGG) task is designed to identify the predicates based on the subject-object pairs.However,existing datasets generally include two imbalance cases: one…
Prototype-guided Cross-task Knowledge Distillation for Large-scale Models
Deng Li, Aming Wu, Yahong Han +1
Recently, large-scale pre-trained models have shown their advantages in many tasks. However, due to the huge computational complexity and storage requirements, it is challenging to…
Vector-Decomposed Disentanglement for Domain-Invariant Object Detection
Aming Wu, Rui Liu, Yahong Han +2
To improve the generalization of detectors, for domain adaptive object detection (DAOD), recent advances mainly explore aligning feature-level distributions between the source and…
Domain-Smoothing Network for Zero-Shot Sketch-Based Image Retrieval
Zhipeng Wang, Hao Wang, Jiexi Yan +2
Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is a novel cross-modal retrieval task, where abstract sketches are used as queries to retrieve natural images under zero-shot scena…
Universal-Prototype Enhancing for Few-Shot Object Detection
Aming Wu, Yahong Han, Linchao Zhu +1
Few-shot object detection (FSOD) aims to strengthen the performance of novel object detection with few labeled samples. To alleviate the constraint of few samples, enhancing the ge…
Hierarchical Memory Decoding for Video Captioning
Aming Wu, Yahong Han
Recent advances of video captioning often employ a recurrent neural network (RNN) as the decoder. However, RNN is prone to diluting long-term information. Recent works have demonst…
Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement
Aming Wu, Yahong Han, Linchao Zhu +1
Most state-of-the-art methods of object detection suffer from poor generalization ability when the training and test data are from different domains, e.g., with different styles. T…