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20182026
most citedEfficient Video Classification Using Fewer Frames

4 citations · 5 across the 3 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

V-REX: Benchmarking Exploratory Visual Reasoning via Chain-of-Questions

Chenrui Fan, Yijun Liang, Shweta Bhardwaj +3

While many vision-language models (VLMs) are developed to answer well-defined, straightforward questions with highly specified targets, as in most benchmarks, they often struggle i…

cs.CV2025

ColorBench: Can VLMs See and Understand the Colorful World? A Comprehensive Benchmark for Color Perception, Reasoning, and Robustness

Yijun Liang, Ming Li, Chenrui Fan +7

Color plays an important role in human perception and usually provides critical clues in visual reasoning. However, it is unclear whether and how vision-language models (VLMs) can…

cs.CV2024

Diffusion Curriculum: Synthetic-to-Real Data Curriculum via Image-Guided Diffusion

Yijun Liang, Shweta Bhardwaj, Tianyi Zhou

Low-quality or scarce data has posed significant challenges for training deep neural networks in practice. While classical data augmentation cannot contribute very different new da…

cs.CV20194 cited

Efficient Video Classification Using Fewer Frames

Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra

Recently,there has been a lot of interest in building compact models for video classification which have a small memory footprint (<1 GB). While these models are compact, they typi…

cs.CV2018

I Have Seen Enough: A Teacher Student Network for Video Classification Using Fewer Frames

Shweta Bhardwaj, Mitesh M. Khapra

Over the past few years, various tasks involving videos such as classification, description, summarization and question answering have received a lot of attention. Current models f…

cs.CV2018

Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks

Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra +1

Recently there has been a lot of work on pruning filters from deep convolutional neural networks (CNNs) with the intention of reducing computations. The key idea is to rank the fil…