22 citations · 65 across the 22 of their papers we have counts for
22 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…
Technical Report for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Pretraining-Diverse Ensemble of Foundation Vision Encoders for Robust Outdoor Scene Understanding
Boyan Wang, Yongxi Huang, Wenjing Li +4
This report presents our solution for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge, which requires parsing unstructured outdoor scenes from four camera platf…
RATopo: Improving Lane Topology Reasoning via Redundancy Assignment
Han Li, Shaofei Huang, Longfei Xu +3
Lane topology reasoning plays a critical role in autonomous driving by modeling the connections among lanes and the topological relationships between lanes and traffic elements. Mo…
DOMR: Establishing Cross-View Segmentation via Dense Object Matching
Jitong Liao, Yulu Gao, Shaofei Huang +4
Cross-view object correspondence involves matching objects between egocentric (first-person) and exocentric (third-person) views. It is a critical yet challenging task for visual u…
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…
Anchor3DLane++: 3D Lane Detection via Sample-Adaptive Sparse 3D Anchor Regression
Shaofei Huang, Zhenwei Shen, Zehao Huang +4
In this paper, we focus on the challenging task of monocular 3D lane detection. Previous methods typically adopt inverse perspective mapping (IPM) to transform the Front-Viewed (FV…
FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction
Runze He, Kai Ma, Linjiang Huang +6
Introducing user-specified visual concepts in image editing is highly practical as these concepts convey the user's intent more precisely than text-based descriptions. We propose F…
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…
Mask-Enhanced Segment Anything Model for Tumor Lesion Semantic Segmentation
Hairong Shi, Songhao Han, Shaofei Huang +6
Tumor lesion segmentation on CT or MRI images plays a critical role in cancer diagnosis and treatment planning. Considering the inherent differences in tumor lesion segmentation da…
Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation
Yuanbin Wang, Shaofei Huang, Yulu Gao +5
Traditional 3D segmentation methods can only recognize a fixed range of classes that appear in the training set, which limits their application in real-world scenarios due to the l…
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…
Discovering Sounding Objects by Audio Queries for Audio Visual Segmentation
Shaofei Huang, Han Li, Yuqing Wang +5
Audio visual segmentation (AVS) aims to segment the sounding objects for each frame of a given video. To distinguish the sounding objects from silent ones, both audio-visual semant…
Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection
Shaofei Huang, Zhenwei Shen, Zehao Huang +5
Monocular 3D lane detection is a challenging task due to its lack of depth information. A popular solution is to first transform the front-viewed (FV) images or features into the b…
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…
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…