3 citations · 4 across the 7 of their papers we have counts for
9 papers
THG-Omni: Traceable Human-Centric Graph Supervision for Video Reasoning
Jisheng Dang, Kai Wei, Ronghao Lin +6
Omni-modal models can answer questions about video, but their predictions rarely show which participant, event, or interval supports an answer. Moreover, answer-level supervision a…
ObjEmbed: Towards Universal Multimodal Object Embeddings
Shenghao Fu, Yukun Su, Fengyun Rao +3
Aligning objects with corresponding textual descriptions is a fundamental challenge and a realistic requirement in vision-language understanding. While recent multimodal embedding…
WeDetect: Fast Open-Vocabulary Object Detection as Retrieval
Shenghao Fu, Yukun Su, Fengyun Rao +3
Open-vocabulary object detection aims to detect arbitrary classes via text prompts. Methods without cross-modal fusion layers (non-fusion) offer faster inference by treating recogn…
LOVE-R1: Advancing Long Video Understanding with an Adaptive Zoom-in Mechanism via Multi-Step Reasoning
Shenghao Fu, Qize Yang, Yuan-Ming Li +3
Long video understanding is still challenging for recent Large Video-Language Models (LVLMs) due to the conflict between long-form temporal understanding and detailed spatial perce…
Reinforcing Video Reasoning with Focused Thinking
Jisheng Dang, Jingze Wu, Teng Wang +6
Recent advancements in reinforcement learning, particularly through Group Relative Policy Optimization (GRPO), have significantly improved multimodal large language models for comp…
A Hierarchical Semantic Distillation Framework for Open-Vocabulary Object Detection
Shenghao Fu, Junkai Yan, Qize Yang +3
Open-vocabulary object detection (OVD) aims to detect objects beyond the training annotations, where detectors are usually aligned to a pre-trained vision-language model, eg, CLIP,…
Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models
Shenghao Fu, Junkai Yan, Qize Yang +3
Recent vision foundation models can extract universal representations and show impressive abilities in various tasks. However, their application on object detection is largely over…
Loc4Plan: Locating Before Planning for Outdoor Vision and Language Navigation
Huilin Tian, Jingke Meng, Wei-Shi Zheng +3
Vision and Language Navigation (VLN) is a challenging task that requires agents to understand instructions and navigate to the destination in a visual environment.One of the key ch…
Transformer for Object Re-Identification: A Survey
Mang Ye, Shuoyi Chen, Chenyue Li +3
Object Re-identification (Re-ID) aims to identify specific objects across different times and scenes, which is a widely researched task in computer vision. For a prolonged period,…