activity
20152026
most citedVoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

318 citations · 442 across the 22 of their papers we have counts for

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16 papers · 1 filter

cs.CV2026

LiTo: Surface Light Field Tokenization

Jen-Hao Rick Chang, Xiaoming Zhao, Dorian Chan +1

We propose a 3D latent representation that jointly models object geometry and view-dependent appearance. Most prior works focus on either reconstructing 3D geometry or predicting v…

cs.CV2025

MobileCLIP2: Improving Multi-Modal Reinforced Training

Fartash Faghri, Pavan Kumar Anasosalu Vasu, Cem Koc +4

Foundation image-text models such as CLIP with zero-shot capabilities enable a wide array of applications. MobileCLIP is a recent family of image-text models at 3-15ms latency and…

cs.CV2025

FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations

Cheng-Yu Hsieh, Pavan Kumar Anasosalu Vasu, Fartash Faghri +5

Visual understanding is inherently contextual -- what we focus on in an image depends on the task at hand. For instance, given an image of a person holding a bouquet of flowers, we…

cs.CV2024

3D Shape Tokenization via Latent Flow Matching

Jen-Hao Rick Chang, Yuyang Wang, Miguel Angel Bautista Martin +4

We introduce a latent 3D representation that models 3D surfaces as probability density functions in 3D, i.e., p(x,y,z), with flow-matching. Our representation is specifically desig…

cs.CV2024

FastVLM: Efficient Vision Encoding for Vision Language Models

Pavan Kumar Anasosalu Vasu, Fartash Faghri, Chun-Liang Li +8

Scaling the input image resolution is essential for enhancing the performance of Vision Language Models (VLMs), particularly in text-rich image understanding tasks. However, popula…

cs.CV2024

Synth4Seg -- Learning Defect Data Synthesis for Defect Segmentation using Bi-level Optimization

Shancong Mou, Raviteja Vemulapalli, Shiyu Li +8

Defect segmentation is crucial for quality control in advanced manufacturing, yet data scarcity poses challenges for state-of-the-art supervised deep learning. Synthetic defect dat…