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Changbo Wang

16 accepted papers

2026

Audio-VLA: Adding Contact Audio Perception to Vision-Language-Action Model for Robotic Manipulation

ICRA 2026poster

The Vision-Language-Action models (VLA) have achieved significant advances in robotic manipulation recently. However, vision-only VLA models create fundamental limitations, particularly in perceiving interactive and manipulation dynamic processes. This paper proposes Audio-VLA, a multimodal manipula…

2026

GT2-GS: Geometry-aware Texture Transfer for Gaussian Splatting

AAAI 2026technical

Transferring 2D textures onto complex 3D scenes plays a vital role in enhancing the efficiency and controllability of 3D multimedia content creation. However, existing 3D style transfer methods primarily focus on transferring abstract artistic styles to 3D scenes. These methods often overlook the ge

Cited by 0SourcePDFScholar
2026

MPJudge: Towards Perceptual Assessment of Music-Induced Paintings

AAAI 2026technical

Music-induced painting is a unique artistic practice, where visual artworks are created under the influence of music. Evaluating whether a painting faithfully reflects the music that inspired it poses a challenging perceptual assessment task. Existing methods primarily rely on emotion recognition mo

Cited by 0SourcePDFScholar
2026

ReactDance: Hierarchical Representation for High-Fidelity and Coherent Long-Form Reactive Dance Generation

ICLR 2026poster

Reactive dance generation (RDG), the task of generating a dance conditioned on a lead dancer's motion, holds significant promise for enhancing human-robot interaction and immersive digital entertainment. Despite progress in duet synchronization and motion-music alignment, two key challenges remain:…

Cited by 0SourceScholar
2025

DPSN: Dual Prior Knowledge Induced Tactile paving and Obstacle Joint Segmentation Network

IROS 2025

Accurate semantic segmentation of both tactile paving and the obstacle is crucial for the safe mobility of visually impaired individuals. However, existing methods face two major challenges: (i) discontinuous segmentation fragments; (ii) Inaccurate obstacle recognition. To address challenge (i), we

Cited by 0SourceScholar
2025

Motion-Zero: A Zero-Shot Trajectory Control Framework of Moving Object for Diffusion-Based Video Generation

AAAI 2025technical

Recent large-scale pre-trained diffusion models have demonstrated a powerful generative ability to produce high-quality videos from detailed text descriptions. However, exerting control over the motion of objects in videos generated by any video diffusion model remains a challenging problem. In this…

Cited by 0SourcePDFScholar
2025

Robust Message Embedding via Attention Flow-Based Steganography

CVPR 2025poster

Image steganography can hide information in a host image and obtain a stego image that is perceptually indistinguishable from the original one. This technique has tremendous potential in scenarios like copyright protection and information retrospection. Some previous studies have proposed to enhance…

2025

TextCenGen: Attention-Guided Text-Centric Background Adaptation for Text-to-Image Generation

ICML 2025poster

Text-to-image (T2I) generation has made remarkable progress in producing high-quality images, but a fundamental challenge remains: creating backgrounds that naturally accommodate text placement without compromising image quality. This capability is non-trivial for real-world applications like graph…

2024

AACP: Aesthetics Assessment of Children’s Paintings Based on Self-Supervised Learning

AAAI 2024technical

The Aesthetics Assessment of Children's Paintings (AACP) is an important branch of the image aesthetics assessment (IAA), playing a significant role in children's education. This task presents unique challenges, such as limited available data and the requirement for evaluation metrics from multiple…

Cited by 1SourcePDFScholar
2024

CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning

CVPR 2024highlight

3D Scene Graph Generation (3DSGG) aims to classify objects and their predicates within 3D point cloud scenes. However current 3DSGG methods struggle with two main challenges. 1) The dependency on labor-intensive ground-truth annotations. 2) Closed-set classes training hampers the recognition of nove…

Cited by 8SourcePDFScholar
2024

ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model

NeurIPS 2024poster

Visual object tracking aims to locate a targeted object in a video sequence based on an initial bounding box. Recently, Vision-Language~(VL) trackers have proposed to utilize additional natural language descriptions to enhance versatility in various applications. However, VL trackers are still infer…

Cited by 6SourcePDFScholar
2024

Kumaraswamy Wavelet for Heterophilic Scene Graph Generation

AAAI 2024technical

Graph neural networks (GNNs) has demonstrated its capabilities in the field of scene graph generation (SGG) by updating node representations from neighboring nodes. Actually it can be viewed as a form of low-pass filter in the spatial domain, which smooths node feature representation and retains com…

Cited by 2SourcePDFScholar
2024

Multi-Prototype Space Learning for Commonsense-Based Scene Graph Generation

AAAI 2024technical

In the domain of scene graph generation, modeling commonsense as a single-prototype representation has been typically employed to facilitate the recognition of infrequent predicates. However, a fundamental challenge lies in the large intra-class variations of the visual appearance of predicates, res…

Cited by 6SourcePDFScholar
2023

Explicit Invariant Feature Induced Cross-Domain Crowd Counting

AAAI 2023technical

Cross-domain crowd counting has shown progressively improved performance. However, most methods fail to explicitly consider the transferability of different features between source and target domains. In this paper, we propose an innovative explicit Invariant Feature induced Cross-domain Knowledge T…

2019

Transferring Grasp Configurations using Active Learning and Local Replanning

ICRA 2019poster

We present a new approach to transfer grasp configurations from prior example objects to novel objects. We assume the novel and example objects have the same topology and similar shapes. We perform 3D segmentation on these objects using geometric and semantic shape characteristics. We compute a gras…

Cited by 22SourceScholar