22 citations · 59 across the 18 of their papers we have counts for
18 papers
Acoustically Grounded Cost Learning for Open-Vocabulary Audio-Visual Semantic Segmentation
Tianrui Hui, Shaofei Huang, Qisong Han +6
Open-Vocabulary Audio-Visual Semantic Segmentation (OV-AVSS) aims to perform pixel-level segmentation of sound-emitting objects from an open set of categories. The previous method…
Parse, Search, and Confirmation: Training-Free Aerial Vision-and-Dialog Navigation with Chain-of-Thought Reasoning and Structured Spatial Memory
Yu Qi, Hongyu Li, Shaofei Huang +6
In this paper, we tackle the Aerial Vision-and-Dialog Navigation (AVDN) task in the training-free setting for resource-efficient high-altitude UAV navigation.Naively applying MLLMs…
Revisiting Audio-Visual Segmentation with Vision-Centric Transformer
Shaofei Huang, Rui Ling, Tianrui Hui +6
Audio-Visual Segmentation (AVS) aims to segment sound-producing objects in video frames based on the associated audio signal. Prevailing AVS methods typically adopt an audio-centri…
LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding
Hongyu Li, Jinyu Chen, Ziyu Wei +5
Recent advancements in multimodal large language models (MLLMs) have shown promising results, yet existing approaches struggle to effectively handle both temporal and spatial local…
Dynamic Prompting of Frozen Text-to-Image Diffusion Models for Panoptic Narrative Grounding
Hongyu Li, Tianrui Hui, Zihan Ding +5
Panoptic narrative grounding (PNG), whose core target is fine-grained image-text alignment, requires a panoptic segmentation of referred objects given a narrative caption. Previous…
Unleashing the Temporal-Spatial Reasoning Capacity of GPT for Training-Free Audio and Language Referenced Video Object Segmentation
Shaofei Huang, Rui Ling, Hongyu Li +5
In this paper, we propose an Audio-Language-Referenced SAM 2 (AL-Ref-SAM 2) pipeline to explore the training-free paradigm for audio and language-referenced video object segmentati…
Customize your NeRF: Adaptive Source Driven 3D Scene Editing via Local-Global Iterative Training
Runze He, Shaofei Huang, Xuecheng Nie +6
In this paper, we target the adaptive source driven 3D scene editing task by proposing a CustomNeRF model that unifies a text description or a reference image as the editing prompt…
Enriching Phrases with Coupled Pixel and Object Contexts for Panoptic Narrative Grounding
Tianrui Hui, Zihan Ding, Junshi Huang +5
Panoptic narrative grounding (PNG) aims to segment things and stuff objects in an image described by noun phrases of a narrative caption. As a multimodal task, an essential aspect…
Cross-Modality Domain Adaptation for Freespace Detection: A Simple yet Effective Baseline
Yuanbin Wang, Leyan Zhu, Shaofei Huang +4
As one of the fundamental functions of autonomous driving system, freespace detection aims at classifying each pixel of the image captured by the camera as drivable or non-drivable…
PPMN: Pixel-Phrase Matching Network for One-Stage Panoptic Narrative Grounding
Zihan Ding, Zi-han Ding, Tianrui Hui +4
Panoptic Narrative Grounding (PNG) is an emerging task whose goal is to segment visual objects of things and stuff categories described by dense narrative captions of a still image…
Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation
Zihan Ding, Tianrui Hui, Junshi Huang +3
Referring video object segmentation aims to predict foreground labels for objects referred by natural language expressions in videos. Previous methods either depend on 3D ConvNets…
A Keypoint-based Global Association Network for Lane Detection
Jinsheng Wang, Yinchao Ma, Shaofei Huang +4
Lane detection is a challenging task that requires predicting complex topology shapes of lane lines and distinguishing different types of lanes simultaneously. Earlier works follow…
TransRefer3D: Entity-and-Relation Aware Transformer for Fine-Grained 3D Visual Grounding
Dailan He, Yusheng Zhao, Junyu Luo +4
Recently proposed fine-grained 3D visual grounding is an essential and challenging task, whose goal is to identify the 3D object referred by a natural language sentence from other…
Cross-Modal Progressive Comprehension for Referring Segmentation
Si Liu, Tianrui Hui, Shaofei Huang +3
Given a natural language expression and an image/video, the goal of referring segmentation is to produce the pixel-level masks of the entities described by the subject of the expre…
Collaborative Spatial-Temporal Modeling for Language-Queried Video Actor Segmentation
Tianrui Hui, Shaofei Huang, Si Liu +5
Language-queried video actor segmentation aims to predict the pixel-level mask of the actor which performs the actions described by a natural language query in the target frames. E…
ORDNet: Capturing Omni-Range Dependencies for Scene Parsing
Shaofei Huang, Si Liu, Tianrui Hui +4
Learning to capture dependencies between spatial positions is essential to many visual tasks, especially the dense labeling problems like scene parsing. Existing methods can effect…
Linguistic Structure Guided Context Modeling for Referring Image Segmentation
Tianrui Hui, Si Liu, Shaofei Huang +4
Referring image segmentation aims to predict the foreground mask of the object referred by a natural language sentence. Multimodal context of the sentence is crucial to distinguish…
Referring Image Segmentation via Cross-Modal Progressive Comprehension
Shaofei Huang, Tianrui Hui, Si Liu +5
Referring image segmentation aims at segmenting the foreground masks of the entities that can well match the description given in the natural language expression. Previous approach…