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20162024
most citedQKD: Quantization-aware Knowledge Distillation

47 citations · 176 across the 19 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 8 cited

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…

cs.RO2024★ 27 cited

SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection

Yifu Tao, Yash Bhalgat, Lanke Frank Tarimo Fu +3

We present a neural-field-based large-scale reconstruction system that fuses lidar and vision data to generate high-quality reconstructions that are geometrically accurate and capt…

cs.CV2024

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),…