13 citations · 13 across the 11 of their papers we have counts for
14 papers
Self-Prophetic Decoding to Unlock Visual Search in LVLMs
Zhendong He, Qiyuan Dai, Guanbin Li +2
Large Vision-Language Models (LVLMs) are rapidly evolving toward true multimodal reasoning, with visual search representing a concrete instantiation of the thinking-with-images par…
LookasideVLN: Direction-Aware Aerial Vision-and-Language Navigation
Yuwei Ning, Ganlong Zhao, Yipeng Qin +4
Aerial Vision-and-Language Navigation (Aerial VLN) enables unmanned aerial vehicles (UAVs) to follow natural language instructions and navigate complex urban environments. While re…
OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives
Zedong Dan, Zijie Wang, Wei Zhang +6
Offline vectorized maps constitute critical infrastructure for high-precision autonomous driving and mapping services. Existing approaches rely predominantly on single ego-vehicle…
DreamShot: Personalized Storyboard Synthesis with Video Diffusion Prior
Junjia Huang, Binbin Yang, Pengxiang Yan +6
Storyboard synthesis plays a crucial role in visual storytelling, aiming to generate coherent shot sequences that visually narrate cinematic events with consistent characters, scen…
Sim-DETR: Unlock DETR for Temporal Sentence Grounding
Jiajin Tang, Zhengxuan Wei, Yuchen Zhu +4
Temporal sentence grounding aims to identify exact moments in a video that correspond to a given textual query, typically addressed with detection transformer (DETR) solutions. How…
Free-MoRef: Instantly Multiplexing Context Perception Capabilities of Video-MLLMs within Single Inference
Kuo Wang, Quanlong Zheng, Junlin Xie +6
Video Multimodal Large Language Models~(Video-MLLM) have achieved remarkable advancements in video understanding tasks. However, constrained by the context length limitation in the…
DreamFuse: Adaptive Image Fusion with Diffusion Transformer
Junjia Huang, Pengxiang Yan, Jiyang Liu +5
Image fusion seeks to seamlessly integrate foreground objects with background scenes, producing realistic and harmonious fused images. Unlike existing methods that directly insert…
VTON 360: High-Fidelity Virtual Try-On from Any Viewing Direction
Zijian He, Yuwei Ning, Yipeng Qin +4
Virtual Try-On (VTON) is a transformative technology in e-commerce and fashion design, enabling realistic digital visualization of clothing on individuals. In this work, we propose…
DAGSM: Disentangled Avatar Generation with GS-enhanced Mesh
Jingyu Zhuang, Di Kang, Linchao Bao +2
Text-driven avatar generation has gained significant attention owing to its convenience. However, existing methods typically model the human body with all garments as a single 3D m…
High-fidelity and Lip-synced Talking Face Synthesis via Landmark-based Diffusion Model
Weizhi Zhong, Junfan Lin, Peixin Chen +2
Audio-driven talking face video generation has attracted increasing attention due to its huge industrial potential. Some previous methods focus on learning a direct mapping from au…
Style-Preserving Lip Sync via Audio-Aware Style Reference
Weizhi Zhong, Jichang Li, Yinqi Cai +4
Audio-driven lip sync has recently drawn significant attention due to its widespread application in the multimedia domain. Individuals exhibit distinct lip shapes when speaking the…
MarvelOVD: Marrying Object Recognition and Vision-Language Models for Robust Open-Vocabulary Object Detection
Kuo Wang, Lechao Cheng, Weikai Chen +4
Learning from pseudo-labels that generated with VLMs~(Vision Language Models) has been shown as a promising solution to assist open vocabulary detection (OVD) in recent studies. Ho…
Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI
Yang Liu, Weixing Chen, Yongjie Bai +4
Embodied Artificial Intelligence (Embodied AI) is crucial for achieving Artificial General Intelligence (AGI) and serves as a foundation for various applications (e.g., intelligent…
Learning Background Prompts to Discover Implicit Knowledge for Open Vocabulary Object Detection
Jiaming Li, Jiacheng Zhang, Jichang Li +4
Open vocabulary object detection (OVD) aims at seeking an optimal object detector capable of recognizing objects from both base and novel categories. Recent advances leverage knowl…