8 papers
Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM
Amol Harsh, Zongyan Han, Jean Lahoud +5
Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to the referred 3D region, whil…
Composed Object Retrieval: Object-level Retrieval via Composed Expressions
Tong Wang, Guanyu Yang, Nian Liu +4
Retrieving fine-grained visual content based on user intent remains a challenge in multimodal systems. Although current Composed Image Retrieval (CIR) methods combine reference ima…
Audit After Segmentation: Reference-Free Mask Quality Assessment for Language-Referred Audio-Visual Segmentation
Jinxing Zhou, Yanghao Zhou, Yaoting Wang +5
Language-referred audio-visual segmentation (Ref-AVS) aims to segment target objects described by natural language by jointly reasoning over video, audio, and text. Beyond generati…
Thinking Beyond Labels: Vocabulary-Free Fine-Grained Recognition using Reasoning-Augmented LMMs
Dmitry Demidov, Zaigham Zaheer, Zongyan Han +2
Vocabulary-free fine-grained image recognition aims to distinguish visually similar categories within a meta-class without a fixed, human-defined label set. Existing solutions for…
Bring Your Dreams to Life: Continual Text-to-Video Customization
Jiahua Dong, Xudong Wang, Wenqi Liang +7
Customized text-to-video generation (CTVG) has recently witnessed great progress in generating tailored videos from user-specific text. However, most CTVG methods assume that perso…
OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning
Zongyan Han, Jiale Cao, Shuo Chen +3
Open-Vocabulary Segmentation (OVS) has drawn increasing attention for its capacity to generalize segmentation beyond predefined categories. However, existing methods typically pred…