activity
20182023
most citedCLIP-Count: Towards Text-Guided Zero-Shot Object Counting

75 citations · 262 across the 24 of their papers we have counts for

collaborators

24 papers

cs.AI2023

Measuring Acoustics with Collaborative Multiple Agents

Yinfeng Yu, Changan Chen, Lele Cao +2

As humans, we hear sound every second of our life. The sound we hear is often affected by the acoustics of the environment surrounding us. For example, a spacious hall leads to mor…

cs.CL2023

Long-Term Ad Memorability: Understanding & Generating Memorable Ads

Harini SI, Somesh Singh, Yaman K Singla +5

Despite the importance of long-term memory in marketing and brand building, until now, there has been no large-scale study on the memorability of ads. All previous memorability stu…

cs.CV2023

Replay: Multi-modal Multi-view Acted Videos for Casual Holography

Roman Shapovalov, Yanir Kleiman, Ignacio Rocco +6

We introduce Replay, a collection of multi-view, multi-modal videos of humans interacting socially. Each scene is filmed in high production quality, from different viewpoints with…

cs.MM2023★ 2 cited

Self-Supervised Visual Acoustic Matching

Arjun Somayazulu, Changan Chen, Kristen Grauman

Acoustic matching aims to re-synthesize an audio clip to sound as if it were recorded in a target acoustic environment. Existing methods assume access to paired training data, wher…

cs.CV2023★ 75 cited

CLIP-Count: Towards Text-Guided Zero-Shot Object Counting

Ruixiang Jiang, Lingbo Liu, Changwen Chen

Recent advances in visual-language models have shown remarkable zero-shot text-image matching ability that is transferable to downstream tasks such as object detection and segmenta…

cs.GR2023★ 5 cited

Learning Audio-Driven Viseme Dynamics for 3D Face Animation

Linchao Bao, Haoxian Zhang, Yue Qian +4

We present a novel audio-driven facial animation approach that can generate realistic lip-synchronized 3D facial animations from the input audio. Our approach learns viseme dynamic…