2 citations · 3 across the 8 of their papers we have counts for
8 papers · 1 filter
LibraGen: Playing a Balance Game in Subject-Driven Video Generation
Jiahao Zhu, Shanshan Lao, Lijie Liu +10
With the advancement of video generation foundation models (VGFMs), customized generation, particularly subject-to-video (S2V), has attracted growing attention. However, a key chal…
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…
ViSpeak: Visual Instruction Feedback in Streaming Videos
Shenghao Fu, Qize Yang, Yuan-Ming Li +6
Recent advances in Large Multi-modal Models (LMMs) are primarily focused on offline video understanding. Instead, streaming video understanding poses great challenges to recent mod…
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,…
LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models
Shenghao Fu, Qize Yang, Qijie Mo +5
Recent open-vocabulary detectors achieve promising performance with abundant region-level annotated data. In this work, we show that an open-vocabulary detector co-training with a…
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…