7 citations · 14 across the 14 of their papers we have counts for
12 papers · 1 filter
MPT: Motion Prompt Tuning for Micro-Expression Recognition
Jiateng Liu, Hengcan Shi, Feng Chen +4
Micro-expression recognition (MER) is crucial in the affective computing field due to its wide application in medical diagnosis, lie detection, and criminal investigation. Despite…
DrVideo: Document Retrieval Based Long Video Understanding
Ziyu Ma, Chenhui Gou, Hengcan Shi +4
Most of the existing methods for video understanding primarily focus on videos only lasting tens of seconds, with limited exploration of techniques for handling long videos. The in…
JRDB-PanoTrack: An Open-world Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments
Duy-Tho Le, Chenhui Gou, Stavya Datta +4
Autonomous robot systems have attracted increasing research attention in recent years, where environment understanding is a crucial step for robot navigation, human-robot interacti…
DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation
Duy-Tho Le, Hengcan Shi, Jianfei Cai +1
Diffusion models have recently gained prominence as powerful deep generative models, demonstrating unmatched performance across various domains. However, their potential in multi-s…
Open-Vocabulary Scene Text Recognition via Pseudo-Image Labeling and Margin Loss
Xuhua Ren, Hengcan Shi, Jin Li
Scene text recognition is an important and challenging task in computer vision. However, most prior works focus on recognizing pre-defined words, while there are various out-of-voc…
Unified Open-Vocabulary Dense Visual Prediction
Hengcan Shi, Munawar Hayat, Jianfei Cai
In recent years, open-vocabulary (OV) dense visual prediction (such as OV object detection, semantic, instance and panoptic segmentations) has attracted increasing research attenti…
Open-Vocabulary Object Detection via Scene Graph Discovery
Hengcan Shi, Munawar Hayat, Jianfei Cai
In recent years, open-vocabulary (OV) object detection has attracted increasing research attention. Unlike traditional detection, which only recognizes fixed-category objects, OV d…
Class Enhancement Losses with Pseudo Labels for Zero-shot Semantic Segmentation
Son Duy Dao, Hengcan Shi, Dinh Phung +1
Recent mask proposal models have significantly improved the performance of zero-shot semantic segmentation. However, the use of a `background' embedding during training in these me…
Transformer Scale Gate for Semantic Segmentation
Hengcan Shi, Munawar Hayat, Jianfei Cai
Effectively encoding multi-scale contextual information is crucial for accurate semantic segmentation. Existing transformer-based segmentation models combine features across scales…
ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues
Hengcan Shi, Munawar Hayat, Yicheng Wu +1
Object proposal generation is an important and fundamental task in computer vision. In this paper, we propose ProposalCLIP, a method towards unsupervised open-category object propo…
Unpaired Referring Expression Grounding via Bidirectional Cross-Modal Matching
Hengcan Shi, Munawar Hayat, Jianfei Cai
Referring expression grounding is an important and challenging task in computer vision. To avoid the laborious annotation in conventional referring grounding, unpaired referring gr…
Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network
Duy-Tho Le, Hengcan Shi, Hamid Rezatofighi +1
Efficiently and accurately detecting people from 3D point cloud data is of great importance in many robotic and autonomous driving applications. This fundamental perception task is…