47 citations · 83 across the 4 of their papers we have counts for
10 papers · 1 filter
3D-Aware Instance Segmentation and Tracking in Egocentric Videos
Yash Bhalgat, Vadim Tschernezki, Iro Laina +3
Egocentric videos present unique challenges for 3D scene understanding due to rapid camera motion, frequent object occlusions, and limited object visibility. This paper introduces…
Reproducibility Study of CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification
Manan Shah, Yash Bhalgat
This report is a reproducibility study of the paper "CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification" (Abdelfattah et al, ICCV 2023). Our report makes…
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Xianzheng Ma, Brandon Smart, Yash Bhalgat +14
As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interact…
N2F2: Hierarchical Scene Understanding with Nested Neural Feature Fields
Yash Bhalgat, Iro Laina, João F. Henriques +2
Understanding complex scenes at multiple levels of abstraction remains a formidable challenge in computer vision. To address this, we introduce Nested Neural Feature Fields (N2F2),…
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Yash Bhalgat, Iro Laina, João F. Henriques +2
Instance segmentation in 3D is a challenging task due to the lack of large-scale annotated datasets. In this paper, we show that this task can be addressed effectively by leveragin…
Structured Convolutions for Efficient Neural Network Design
Yash Bhalgat, Yizhe Zhang, Jamie Lin +1
In this work, we tackle model efficiency by exploiting redundancy in the \textit{implicit structure} of the building blocks of convolutional neural networks. We start our analysis…