Publications

Recent advances in multimodal large language models (MLLMs) have expanded research in video understanding, primarily focusing on …

A method implements multimodal four-dimensional panoptic segmentation. The method includes receiving a set of images and a set of point …

4D panoptic segmentation is a challenging but practically useful task that requires every point in a LiDAR point-cloud sequence to be …

The general domain of video segmentation is currently fragmented into different tasks spanning multiple benchmarks. Despite rapid …

Multiple existing benchmarks involve tracking and segmenting objects in video e.g., Video Object Segmentation (VOS) and Multi-Object …

Existing state-of-the-art methods for Video Object Segmentation (VOS) learn low-level pixel-to-pixel correspondences between frames to …

Transformers have become prevalent in computer vision due to their performance and flexibility in modelling complex operations. Of …

Despite receiving significant attention from the research community, the task of segmenting and tracking objects in monocular videos …

The task of Video Instance Segmentation (VIS) involves segmenting, tracking and classifying all object instances present in a given …

The task of object segmentation in videos is usually accomplished by processing appearance and motion information separately using …

Existing methods for instance segmentation in videos typically involve multi-stage pipelines that follow the tracking-by-detection …

In this paper, we present a motion planning framework for humanoid robots that combines whole-body motions as well as footsteps under a …

The task of whole-body motion planning for humanoid robots is challenging due to its high-DOF nature, stability constraints, and the …