Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileAcademic lineage
Possible advisorsa guess from early papers, not confirmed
- Ming–Hsuan YangSuggested from co-authorship
Is this you? Claim this profile to confirm or dismiss it.
Works117 from public data
- The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking1,076
This work constructs a new UAV benchmark focusing on complex scenarios with new level challenges, and is the first time to explore issues in unconstrained scenes comprehensively in UAV based real scenes.
- The Visual Object Tracking VOT2016 Challenge Results776
The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
- 705
- The Visual Object Tracking VOT2014 Challenge Results588
The Visual Object Tracking challenge 2014, VOT2014, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance and introduces a new dataset with full annotation of targets by rotated bounding boxes and per-frame attribute.
- REVERIE: Remote Embodied Visual Referring Expression in Real Indoor Environments551
A dataset of varied and complex robot tasks, described in natural language, in terms of objects visible in a large set of real images, and a novel Interactive Navigator-Pointer model is proposed that provides a strong baseline on the task.
- VLN↻BERT: A Recurrent Vision-and-Language BERT for Navigation503
A recurrent BERT model that is time-aware for use in VLN is proposed that can replace more complex encoder-decoder models to achieve state-of-the-art results and can generalised to other transformer-based architectures.
- AerialVLN: Vision-and-Language Navigation for UAVs208
A new task named AerialVLN is proposed, which is UAV-based and towards outdoor environments, and an extended baseline model based on the widely-used cross-modal-alignment (CMA) navigation methods are proposed.
- Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection143
This work designs a multi-head classification module (each head serves as a classifier) with a diversity loss to maximize the distribution differences of predicted pseudo labels across heads and devise an iterative uncertainty pseudo label refinement strategy, which improves not only the initial pseudo labels but also the updated ones obtained by the desired classifier in the second stage.
- Object-and-Action Aware Model for Visual Language Navigation142
An Object-and-Action Aware Model (OAAM) is proposed that processes these two different forms of natural language based instruction separately and enables each process to match object-centered/action-centered instruction to their own counterpart visual perception/action orientation flexibly.
- 122
- Hierarchical Modular Network for Video Captioning111
A hierarchical modular network to bridge video representations and linguistic semantics from three levels before generating captions is proposed and shows that the proposed method performs favorably against the state-of-the-art models on the two widely-used benchmarks.
- HOP: History-and-Order Aware Pretraining for Vision-and-Language Navigation108
This work proposes a novel history-and-order aware pre-training paradigm (HOP) with VLN-specific objectives that exploit the past observations and support future action prediction to promote the learning of spatio-temporal visual-textual correspondence and the agent's capability of decision making.
- Neighbor-view Enhanced Model for Vision and Language Navigation99
This work proposes a multi-module Neighbor-View Enhanced Model (NvEM) to adaptively incorporate visual contexts from neighbor views for better textual-visual matching of existing methods.
- The Road to Know-Where: An Object-and-Room Informed Sequential BERT for Indoor Vision-Language Navigation95
This work proposes an object-informed sequential BERT to encode visual perceptions and linguistic instructions at the same fine-grained level, namely objects and words, and enables the visual-textual clues to be interpreted in light of the temporal context, which is crucial to multi-round VLN tasks.
- VisDrone-SOT2018: The Vision Meets Drone Single-Object Tracking Challenge Results87
The evaluation protocol of the VisDrone-SOT2018 challenge is presented and the results of a comparison of 22 trackers on the benchmark dataset are presented, which are publicly available on the challenge website.
- 85
- 80
- From Speaker to Dubber: Movie Dubbing with Prosody and Duration Consistency Learning71
This work proposes a two-stage dubbing method that allows the model to first learn pronunciation knowledge before practicing it in movie dubbing, and outperforms several state-of-the-art methods on two primary benchmarks.
- Multi-Attention Network for Compressed Video Referring Object Segmentation69
A multi-attention network which consists of dual-path dual-att attention module and a query-based cross-modal Transformer module designed to extract effective representation from compressed data in three modalities, i.e., I-frame, Motion Vector and Residual is proposed.
- March in Chat: Interactive Prompting for Remote Embodied Referring Expression65
A March-in-Chat (MiC) model that can talk to the LLM on the fly and plan dynamically based on a newly proposed Room-and-Object Aware Scene Perceiver (ROASP) and outperforms the previous state-of-the-art by large margins by SPL and RGSPL metrics on the REVERIE benchmark.
- 61
- Diagnosing Vision-and-Language Navigation: What Really Matters59
This work conducts a series of diagnostic experiments to unveil agents’ focus during navigation and shows that indoor navigation agents refer to both object and direction tokens when making decisions, and Transformer-based agents acquire a better cross-modal understanding of objects and display strong numerical reasoning ability than non-Transformer- based agents.
- Learning to Dub Movies via Hierarchical Prosody Models54
This work proposes a novel movie dubbing architecture to tackle these problems via hierarchical prosody modeling, which bridges the visual information to corresponding speech prosody from three aspects: lip, face, and scene.
- 53
- Point-to-Set Distance Metric Learning on Deep Representations for Visual Tracking52
This paper proposes to integrate the point-to-set/ image- to-imageSet distance metric learning (DML) into visual tracking tasks and take full advantage of all the training samples when determining the best target candidate.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.