activity
20242026
collaborators

7 papers

eess.AS2026

Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios

Changhao Pan, Rui Yang, Han Wang +12

Recent advances in speech generation have enabled high-fidelity synthesis, yet systematic evaluation of models under long-context conditions remains largely underexplored. A compre…

cs.CV2026

Part-Aware Open-Vocabulary 3D Affordance Grounding via Prototypical Semantic and Geometric Alignment

Dongqiang Gou, Xuming He

Grounding natural language questions to functionally relevant regions in 3D objects -- termed language-driven 3D affordance grounding -- is essential for embodied intelligence and…

cs.AI2025

GUI-Rise: Structured Reasoning and History Summarization for GUI Navigation

Tao Liu, Chongyu Wang, Rongjie Li +3

While Multimodal Large Language Models (MLLMs) have advanced GUI navigation agents, current approaches face limitations in cross-domain generalization and effective history utiliza…

cs.CV2024

Relation-aware Hierarchical Prompt for Open-vocabulary Scene Graph Generation

Tao Liu, Rongjie Li, Chongyu Wang +1

Open-vocabulary Scene Graph Generation (OV-SGG) overcomes the limitations of the closed-set assumption by aligning visual relationship representations with open-vocabulary textual…

cs.CV2024

From Pixels to Graphs: Open-Vocabulary Scene Graph Generation with Vision-Language Models

Rongjie Li, Songyang Zhang, Dahua Lin +2

Scene graph generation (SGG) aims to parse a visual scene into an intermediate graph representation for downstream reasoning tasks. Despite recent advancements, existing methods st…

cs.CV2024

Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning

Rongjie Li, Yu Wu, Xuming He

Generative vision-language models (VLMs) have shown impressive performance in zero-shot vision-language tasks like image captioning and visual question answering. However, improvin…

cs.CV2024

DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation

Zeeshan Hayder, Xuming He

Scene graph generation aims to capture detailed spatial and semantic relationships between objects in an image, which is challenging due to incomplete labelling, long-tailed relati…